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SECURITIES AND EXCHANGE COMMISSION
WASHINGTON, D.C. 20549
FORM 10-K
ANNUAL REPORT PURSUANT TO SECTION 13 OR 15(D) OF
THE SECURITIES EXCHANGE ACT OF 1934
FOR THE FISCAL YEAR ENDED DECEMBER 31, 2000
COMMISSION FILE NUMBER: 000-30981
GENAISSANCE PHARMACEUTICALS, INC.
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(Exact Name of Registrant as Specified in Its Charter)
DELAWARE 06-1338846
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(State of Incorporation (IRS Employer
or Organization) Identification No.)
FIVE SCIENCE PARK
NEW HAVEN, CONNECTICUT 06511
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(Address of Principal Executive Offices) (Zip Code)
Securities registered pursuant to Section 12(b) of the Act:
NAME OF EACH EXCHANGE
TITLE OF EACH CLASS ON WHICH REGISTERED
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None None
Securities registered pursuant to Section 12(g) of the Act:
COMMON STOCK, $.001 PAR VALUE
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(Title of Class)
Indicate by check mark whether the registrant (1) has filed all reports required
to be filed by Section 13 or 15(d) of the Securities Act of 1934 during the
preceding 12 months (or for such shorter period that the registrant was required
to file such reports), and (2) has been subject to such filing requirements for
the past 90 days. Yes [X] No [ ]
Indicate by check mark if disclosure of delinquent filers pursuant to Item 405
of Regulation S-K is not contained herein, and will not be contained, to the
best of registrant's knowledge, in definitive proxy or information statements
incorporated by reference in Part III of this Form 10-K or any amendment to this
Form 10-K. [ ]
The aggregate market value of our voting stock held by non-affiliates as of
March 19, 2001 was: $153,704,665.
There were 22,695,327 shares of our common stock outstanding as of March 19,
2001.
DOCUMENTS INCORPORATED BY REFERENCE
Portions of the definitive proxy statement of our 2001 Annual Meeting of
Shareholders to be held on May 22, 2001, which definitive proxy statement will
be filed with the Securities and Exchange Commission not later than 120 days
after the registrant's fiscal year of December 31, 2000, are incorporated by
reference into Part III of this Form 10-K.
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ITEM 1. BUSINESS
COMPANY OVERVIEW
We are a leader in developing technology for applying population
genomics to improve the development, marketing and prescribing of drugs. We
discover genomic markers that can be used to predict which patients will respond
effectively to a drug. We are applying our technology and our clinical
development capabilities to identify which of our genomic markers are predictive
of how patients respond to marketed drugs. We market our technology and our
predictive genomic markers to the pharmaceutical industry as a means of
developing more efficient clinical trials and of improving the sales of existing
drugs, by taking into account the genomic differences that exist between
individuals. In November 2000, we entered into our first collaboration agreement
with Janssen Research Foundation, an affiliate of Johnson & Johnson. In
addition, we market our predictive markers to healthcare providers and payers to
help them make better informed decisions as to which drugs should be prescribed
to specific patients and are suitable for reimbursement. Our technology combines
informatics, genomic markers and an efficient process for analyzing clinical
samples to correlate drug response with a patient's genomic variation.
We believe that a fundamental improvement will occur in the delivery of
healthcare if the pharmaceutical and biotechnology industries begin efficiently
using population genomics. We foresee healthcare providers using knowledge of
each individual's unique genome to predict each individual's response to a drug
as well as disease susceptibility and progression. We believe that the
pharmaceutical industry will use population genomics to design and conduct
smaller and better informed clinical trials. We also see the pharmaceutical
industry applying knowledge based upon our predictive genomic markers to
currently marketed drugs, so as to gain approval for new indications and
maintain or increase market share through differentiation from competing
products and to develop second generation drugs. Ultimately, we believe that our
technology will allow physicians and patients to select specific treatments
based on a patient's genome. Our goal is to have our technology become the
standard for incorporating population genomics throughout the pharmaceutical
process of developing, marketing and prescribing drugs.
INDUSTRY OVERVIEW
The pharmaceutical and healthcare industries face intense pressure to
become more productive and deliver more cost effective healthcare. Two of the
pharmaceutical industry's most challenging issues are the high cost and low
success rate of developing drugs and the need to differentiate approved drugs in
highly competitive markets. At the same time, healthcare providers and payers
are spending a growing proportion of their resources on prescription drugs.
The drug development process is costly and subject to a high failure
rate. The average cost of developing a drug is estimated to be $500 million,
including the cost of unsuccessful drug candidates. Even with recent
technological advances, including advances in areas such as genomics, the
failure rate of clinical trials remains very high. In the United States, only
one in five drug candidates that enters clinical trials reaches the market.
Seventy percent of the drug candidates that enter clinical trials successfully
complete phase I, 33% complete phase II, 25% complete phase III and only 20%
achieve regulatory approval. The decision to enter phase III, the most costly
phase of clinical trials, is generally based upon the results obtained from the
limited number of individuals, often fewer than 200, typically studied in phases
I and II. The typical patient population in phase III is between 1,000 and 5,000
individuals, and the average amount of money spent in a single phase III
clinical trial is estimated to be greater than $40 million.
Approved drugs often face intense competition. The period of market
exclusivity for the first drug in a new therapeutic class is typically much
shorter today than it was a few years ago. Consequently, marketing expenditures
have increased rapidly as companies attempt to maintain or increase market
share. Of the approximately $50 billion spent in 1999 on U.S.-based drug
discovery, development and marketing, the pharmaceutical industry spent over $25
billion on marketing drugs. Marketing departments are also under pressure to
maximize the revenue generated from approved products in order to meet
corporate-wide revenue and earnings goals. In addition, the Boston Consulting
Group reports that it expects large pharmaceutical companies to lose a
substantial portion of their present revenues by 2003 due to the expiration of
patents on existing drugs and the effect of generic drugs on competition. Thus,
in order to maintain revenue growth rates and profitability, pharmaceutical
companies must both improve the success rate of clinical trials and
differentiate their drugs in a crowded market place.
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According to the Health Care Financing Administration, the cost for
prescription drugs in the United States increased from $37.7 billion in 1990 to
$100.6 billion in 1999. In addition, during this same period of time, the
overall percentage of healthcare costs for prescribed drugs increased from 5.4%
to 8.2%. In an attempt to contain the rising cost of drug expenditures,
healthcare providers and payers face the difficult task of deciding which drugs
should be prescribed to specific patients and are suitable for reimbursement.
Healthcare providers make these decisions using medical outcome studies and
economic benefit factors but they do not have any knowledge of which individual
patients are most likely to benefit from a specific drug, if at all. Thus,
healthcare providers and patients would benefit from diagnostic tests that could
predict disease susceptibility, allow for earlier and more appropriate
intervention and predict drug efficacy.
POPULATION GENOMICS
The medical community generally acknowledges that most drugs work more
effectively for some patients than others. The pharmaceutical industry often
poorly understands this variability in patient response. Consequently,
pharmaceutical companies may unnecessarily discontinue further drug development,
fail to obtain regulatory approval for promising drug candidates, or, even if a
drug obtains approval, be unable to market an approved drug effectively or to
obtain approval for third party reimbursement.
Scientists have known for a long time that genomic differences
influence how patients respond to drugs. However, pharmaceutical companies
generally have not considered genomic differences between patients in developing
and implementing clinical trials or in the marketing of approved drugs. If
pharmaceutical companies were able to correlate genomic variation with drug
response in clinical trials, they could improve the drug development and
marketing process. For example, pharmaceutical companies could use the
correlation data from phase I and phase II clinical trials to determine the size
of the patient population that would likely benefit from the drug under
development. They would also know the size of the clinical group needed for a
phase III clinical trial to obtain statistically significant data to support the
clinical development program. The pharmaceutical companies would, therefore,
have a better understanding of the cost required to complete the development of
the drug and the likely economic return on their investment before proceeding to
a phase III clinical trial. In addition, understanding the correlation between
genomic differences and drug response would enable pharmaceutical companies to
improve the marketing of their drugs by identifying those patients for whom
particular drugs are likely to be most effective. Furthermore, healthcare
providers and payers would likely benefit economically from predictive
information that would enable a physician to prescribe the appropriate
medication at the earliest possible time.
Population genomics is the analysis of genomic variation within groups
of people. The genomic blueprint each person inherits from his or her biological
parents determines differences, such as height, hair color, and eye color. Our
DNA, which is composed of four building blocks called nucleotides, encodes the
information responsible for these differences. The relative order, or sequence,
of the four nucleotides determines the information content of the DNA. The
entire DNA content of humans consists of 23 structures called chromosomes and
approximately three billion nucleotides. These nucleotides are organized into at
least 25,000 units of information called genes. The information contained in
genes is translated into a product called a protein.
Humans have two copies of each chromosome. Individuals inherit one set
of the 23 chromosomes, a complete genome, from each parent. Therefore, humans
inherit two copies of the human genome. Differences between siblings arise
because the 23 individual chromosomes can be shuffled in more than eight million
different ways. In addition, during the reproductive process, physical exchange
occurs between regions of each chromosomal pair. Thus, each individual inherits
two versions of each chromosome in a form that is slightly different from that
found in either parent. Likewise, each individual may inherit two different
versions of any specific gene. As a result of this process, there may be
differences between versions of a gene within an individual and among groups of
people. On the other hand, individuals, whether they are related or not, may
inherit similar versions of specific genes. Differences between versions of a
gene, whether within an individual or among groups of people, are referred to as
genomic variation.
Small differences between the DNA sequences of two individuals may
cause profound differences between these two people. Population geneticists
estimate that there is approximately a 0.1% difference in the DNA sequence
between any two individuals; at the DNA level, this 0.1% difference translates
into three million sites of genomic variation. Moreover, in order to predict
drug response, one must not only take into account the genomic variation between
two individuals, but also across diverse groups of people. As few as fifty
people selected from two different geographic regions can have 30 million sites
of genomic variation.
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As scientists better understand genetic variation at the molecular or
genomic level, they are more certain that an individual's response to a drug is
dependent upon that individual's unique genome. In addition, more than one gene
generally determines how an individual responds to a drug. Every drug generally
interacts, directly and indirectly, with a variety of different proteins
produced by different genes. Therefore, in order to predict a specific drug
response, scientists must analyze genomic variation in multiple genes.
A practical approach to understanding why individuals have different
responses to the same drug may be to group individuals together based upon
specific genomic similarity, particularly if the similarity correlates with drug
response or disease susceptibility. This genomic similarity can occur in
unrelated individuals from different geographic regions.
Any approach to commercialize the use of population genomics must:
o take into account that each individual has two versions of every gene;
o recognize that multiple genes are involved in an individual's response to a
drug;
o measure accurately and efficiently substantial genomic variation between
individuals from diverse groups; and
o detect, with sophisticated software programs, the correlation of genomic
variation with a drug response.
SINGLE NUCLEOTIDE POLYMORPHISMS AND HAPLOTYPES
At the DNA level, genomic variation occurs mainly as a result of
variation of a single nucleotide, commonly referred to as a single nucleotide
polymorphism or SNP. Several international efforts are underway which are
intended to serve as the starting point for understanding genomic variation. One
is the Human Genome Project whose scientists have made publicly available a
rough draft of a sequence of a single composite human genome. This sequence
provides a starting point to identify SNPs. Another effort is the SNP
Consortium, an industry sponsored initiative that, together with the Human
Genome Project, has identified 1.42 million SNPs distributed throughout the
human genome. However, geneticists believe that only a small portion of the
human genome constitutes gene information. Thus, only a small number of the SNPs
that have been identified fall within these gene regions of DNA.
Some companies are proposing to correlate genomic variability with drug
response by analyzing individual SNPs. A company that seeks to identify these
correlations using the individual SNP approach, however, must examine blood
samples from thousands of patients and perform a complex statistical analysis to
detect possible predictive markers. This approach may lead to a large number of
markers that, when the company performs subsequent testing, may not correlate
with a drug response.
Geneticists historically studied genetic variation by analyzing the
inheritance of traits within an extended family. Classical population
geneticists coined the term haplotype to describe the physical organization of
genetic variation as its occurs on each pair of chromosomes in an individual.
The haplotype is the standard for measuring genetic variation. At the molecular
level, a haplotype consists of multiple individual SNPs that are organized into
one of the limited number of combinations that actually exist as units of
inheritance in humans. Each haplotype contains significantly more information
than individual, unorganized SNPs. As a result, clinicians need fewer patients
to detect a statistically significant correlation with a drug response if they
use haplotypes rather than individual, unorganized SNPs.
Haplotypes provide:
o an accurate measurement of the genomic variation in each individual's two
genomes;
o a practical method of organizing this genomic variation information;
o an efficient tool for measuring this genomic variation in diverse groups of
people; and
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o enough information to allow clinicians to extract statistically accurate
data from small populations.
Both the Human Genome Project and the SNP Consortium have produced
basic information for use by academic and industrial researchers. However, these
efforts did not:
o determine how SNPs are organized within a gene to constitute a haplotype;
o determine the frequency with which SNPs or haplotypes are found in various
populations; or
o create an informatics interface for using this information in a clinical
setting.
Through the use of haplotypes, together with sophisticated software
programs, pharmaceutical companies could determine with statistical accuracy the
correlation between genomic variation and drug response in a small population of
the size commonly seen in phases I and II of clinical trials and, therefore,
make better informed decisions on whether or not to enter phase III clinical
trials. In addition, understanding the correlation between genomic differences
and drug response would enable pharmaceutical companies to improve the marketing
of their drugs by identifying those patients for whom particular drugs are
likely to be most effective. Furthermore, healthcare providers and payers would
likely benefit economically from predictive information that would enable a
physician to prescribe the appropriate medication at the earliest possible time.
THE GENAISSANCE SOLUTION
We combine sophisticated informatics and proprietary procedures with
state-of-the-art DNA sequencing and genomic variation measurement capabilities
to allow pharmaceutical companies to integrate population genomics into the
development, marketing and prescribing of new and existing medicines. We have
invested considerable resources in constructing a production process to discover
genomic variation with the goal of discovering the range of genomic variation
among all of the pharmaceutically relevant genes. We call this complete solution
our HAP(TM) Technology.
The key components of our HAP(TM) Technology are:
o a database of highly informative, proprietary measures of genomic
variation, or haplotypes, for pharmaceutically relevant genes;
o a proprietary informatics system, including unique algorithms, for
correlating genomic variation with drug response; and
o a cost effective efficient process for measuring genomic variation in
clinical DNA samples.
We designed our HAP(TM) Technology to permit pharmaceutical and
biotechnology companies to use population genomics in a variety of ways for drug
development and commercialization.
DRUG DEVELOPMENT. We designed our HAP(TM)Technology to improve the
success rate of drugs in clinical trials by:
o assessing efficiently the genomic variation among the patients involved in
a clinical trial, thereby permitting pharmaceutical companies to
incorporate genomic variation information into all decisions required
during the course of a clinical trial;
o creating better informed, or "smarter," clinical trials through the design
of protocols which result in the inclusion of those patients most likely to
benefit from the proposed therapeutic product;
o facilitating earlier "go/no-go" decisions on whether to proceed to the next
phase of clinical trial testing which should result in a more efficient use
of clinical resources; and
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o reducing the size and, hence, the cost of late-stage clinical trials by
enrolling a group of patients who are most likely to respond to a drug.
DRUG MARKETING AND PRESCRIBING. We also designed our HAP(TM) Technology
to maximize the value of an approved drug by:
o creating diagnostic tests employing HAP(TM) Markers that are predictive of
drug response, as well as developing supporting software to be used in
tandem with the prescribing and/or marketing of a drug;
o integrating genomic variation information into marketing strategies to
sustain and enhance a market leading position or to address problems such
as poor market penetration, competitive pricing issues, safety, risk of
therapeutic substitution, and limited patent life; and
o targeting new markets and obtaining approval for new indications.
Our HAP Technology may also be useful for improving the drug
discovery process through the selection and validation of drug targets. In
addition, pharmaceutical companies could incorporate data obtained during
clinical trials into the drug discovery process to develop second generation
drugs. If widely adopted, our HAP(TM) Technology could enable the healthcare
system to personalize treatment based upon an individual's unique genome.
We are also applying our HAP(TM) Technology to discover and develop HAP
Markers that are correlated with how patients respond to a marketed drug. We are
investing considerable resources in expanding our clinical development group,
which consists of the following:
o physicians experienced in clinical trial development and pathways of
disease;
o clinical operations personnel experienced in the management of large
parallel clinical trials;
o biostatisticians experienced in the analysis of clinical trial data; and
o regulatory affairs personnel experienced in global product approval
processes.
Our product development process consists of:
o an initial clinical discovery study designed to discover HAP Markers that
appear to be correlated with a differential clinical response;
o a follow up clinical development phase designed to confirm and validate the
identified HAP Marker correlation discovered in the clinical discovery
phase; and
o a commercialization phase in which the intellectual property is configured
into a diagnostic test or other information based products to be offered to
pharmaceutical companies and healthcare providers and payers.
OUR STRATEGY
Our objective is to make our HAP Technology the industry standard for
using genomic variation information throughout the pharmaceutical development,
marketing and prescribing process. The key elements of our strategy include the
following:
COMMERCIALIZE OUR HAP TECHNOLOGY THROUGH OUR HAP2000 PARTNERSHIP
PROGRAM. In November 2000, we entered into our first agreement under the HAP2000
partnership program with Janssen Research Foundation, an affiliate of Johnson &
Johnson. We are in discussions and negotiations with additional pharmaceutical
and biotechnology companies to become partners for our HAP2000 partnership
program. Our HAP2000 program provides access to our HAP Technology, including
access to our proprietary HAP Markers, our DECOGEN informatics system, and our
HAP Typing capabilities. In return, we
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receive annual subscription fees, payments for work on specific drug development
or marketing projects and for HAP Typing. In addition, we expect license,
milestone, and royalty payments for the use of our HAP Markers.
PURSUE MEDNOSTICS OPPORTUNITIES. In our Mednostics programs we are
applying our clinical development expertise and our HAP Technology to develop
proprietary information that will predict which patients will benefit from
currently marketed drugs in selected disease areas. We have targeted disease
areas in large markets with multiple approved drugs having large sales and with
the threat of eminent patent expiration and generic competition. We market our
proprietary information to pharmaceutical companies to allow them to
differentiate their currently approved drugs from competitive products and to
improve the introduction of new products. We also market our proprietary
information to healthcare providers and payers to allow them to make better
informed decisions for each individual patient as to which drug should be
prescribed and reimbursed. By funding our Mednostics programs, we believe that
we can accelerate the development of this proprietary, predictive information
and can market this proprietary information to multiple customers on more
favorable terms. By widely disseminating this information through commercial
arrangements with healthcare providers and payers, as well as pharmaceutical
companies, our goal is to establish our proprietary information as an essential
element of clinical decision making. Over the next twelve months, we expect to
initiate Mednostics programs for multiple specific disease areas involving
numerous marketed drugs.
CONTINUE TO EXPAND OUR CLINICAL GENETICS CAPABILITIES. We have invested
considerable resources to build a clinical development group with the goal of
becoming the leading expert in designing and conducting clinical trails to
derive and validate information required to commercialize genomic markers.
DISCOVER AND PATENT HAP MARKERS FOR ALL OF THE PHARMACEUTICALLY
RELEVANT GENES AND THEIR ASSOCIATION WITH CLINICAL APPLICATIONS. We are seeking
to discover HAP Markers for all of the pharmaceutically relevant genes. We are
filing composition of matter patents to protect HAP Markers, as well as their
association with clinical applications such as drug response, disease risk and
side effects. If we discover and protect these HAP Markers, we believe we will
have created the most comprehensive coverage of informative genomic markers
available. We believe that this coverage of genomic variation would give us a
competitive advantage as the premier source for correlating genomic variation
with drug response. We plan to file method patents covering discoveries we make
relating to prescribing a drug safely and efficaciously or for diagnosing a
patient's predisposition to a particular disease.
CONTINUE IMPROVING AND EXPANDING OUR DECOGEN INFORMATICS SYSTEM. We are
continually expanding the capability of our DECOGEN informatics system with the
goal of establishing it as the industry standard for integrating genomic
variation into the pharmaceutical development and marketing process. We believe
our DECOGEN informatics system is the only platform available that combines
sophisticated genomic variation analysis tools with state-of-the-art clinical
statistics in an intuitive, graphical user interface. In December 2000, we
installed our DECOGEN informatics system at Johnson & Johnson, as part of our
HAP2000 partnership program.
SEEK STRATEGIC ALLIANCES WITH LEADING EQUIPMENT AND INFORMATION
TECHNOLOGY PROVIDERS. We plan to form strategic alliances with research and
diagnostic equipment manufacturers and diagnostic and information technology
companies to expand the applications of our HAP Technology, with the goal of
establishing our HAP Technology as a standard component in the delivery of
healthcare.
INCREASE AWARENESS OF THE IMPACT OF GENE VARIATION ON THE FUTURE
PRACTICE OF MEDICINE. We intend to work closely with regulatory agencies, third
party payers, the medical community and healthcare consumers to build awareness
about the benefits of using genomic variation data in the development, marketing
and prescribing of new and existing drugs. Our goal is to establish our HAP
Technology as the industry standard in the healthcare field for evidence-based
medicine.
OUR COMMERCIAL PROGRAMS
HAP2000 PARTNERSHIP PROGRAM
We have developed a program intended to give pharmaceutical and
biotechnology companies access to our HAP Technology throughout each phase of
drug development and marketing. Each partner will gain access to our proprietary
HAP Markers, our DECOGEN informatics system and our HAP Typing capabilities.
Partners may select a limited number of genes annually for HAP Marker discovery.
We anticipate that each partnership will be for a minimum of three years. While
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we expect to retain all intellectual property rights in HAP Markers discovered
during the partnership, our partners will have the option to receive multiple
exclusive licenses for the use of these HAP Markers for the development of
diagnostic and therapeutic products within specified drug classes and for
particular disease indications.
As part of the HAP2000 program, our partners will gain access to our
HAP Typing facility, which we will use to measure HAP Markers from individual
patient samples provided by our partners. Under our HAP2000 program, we seek to
obtain both near-term and deferred payments including:
o annual subscription fees for access to our DECOGEN informatics system,
including our proprietary HAP Markers;
o fees for research projects focused on development or marketing issues
associated with particular drugs;
o fees for HAP Typing clinical samples supplied by our partners; and
o license fees, milestone payments and royalties based on product sales for
the exclusive use of HAP Markers for drugs within a specific class and for
specific disease indications.
Our first agreement under the HAP2000 partnership program with Janssen
Research Foundation, an affiliate of Johnson & Johnson, is structured in
accordance with the deal template described above.
MEDNOSTICS PROGRAM
In our internally funded Mednostics programs, we apply our clinical
development expertise and our HAP Technology to drugs currently marketed by
third parties. Through our Mednostics programs, we seek to find HAP Markers that
identify individuals who:
o will respond better to a particular drug within a competitive class than to
other drugs in the same class or to one competing class of drugs as
compared to another class of drugs;
o are prone to side effects and adverse reactions; and
o are currently not undergoing therapy for a given disease yet are at risk
and will respond well to a given drug.
Identification of individuals who would benefit from a particular drug
may solidify or improve the market position of a particular drug in a highly
competitive market and assist in obtaining approval for third party
reimbursement. Identification of individuals who are at risk of developing a
side effect may increase patient compliance and expand the market for a drug.
Early identification of individuals who are at risk of developing a particular
disease may improve the treatment for a number of significant diseases and
conditions, including many central nervous system disorders, neurodegenerative
disorders, and cardiovascular disease, and expand the market for already
approved drugs.
In our Mednostics programs, our clinical development group seeks to
discover HAP Markers that are correlated with how a patient responds to a
marketed drug. We choose genes to analyze based upon knowledge of the drug in
question, the drug's known or likely target, the disease, and drug metabolism
considerations. The number of genes we analyze will increase as the costs for
HAP Typing decrease. If we fail to detect a correlation with HAP Markers for a
given gene, we eliminate that gene from further consideration. If we cannot
detect a significant correlation, we analyze additional genes. We then test in a
prospective study any correlation that we detect in order to confirm the
predictability of the HAP Markers.
Our clinical development process consists of an initial clinical
discovery phase in which prospective clinical trials, where the identity of the
drug is known to the clinical investigators, are used to discover HAP Markers
that appear to be correlated with a differential clinical response. These
clinical trials are referred to as open label clinical trials. We intend to
enroll approximately 150 patients for treatment with each of the drugs that will
be compared in a therapeutic class. We expect that the clinical discovery phase
will take from one to one and one-half years, depending on the disease area and
the drug being tested. At the conclusion of this phase, we expect that we will
have identified HAP Markers that
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appear to be correlated with a clinical response such as efficacy or safety of a
drug at varying doses as well as disease susceptibility and progression.
We will then proceed to confirm and validate the identified HAP Marker
correlation in a clinical development phase. We intend to perform prospective
clinical trials, which are open label or where the identity of the drug is not
known to the clinical investigators, and where the identity of a patient's HAP
Markers is unknown to the clinical investigators. We intend to enroll 150 to 300
patients for treatment with each of the drugs that will be compared in a
therapeutic class. We expect that the clinical development phase will take from
one to two years, depending on the disease area and the drug being tested. At
the conclusion of this phase, we expect that we will have produced validated HAP
Markers that are correlated with a clinical response and suitable for
commercialization.
As an example of our Mednostics programs, we are applying our HAP
Technology to the statin class of drugs, which doctors use to treat patients
with high cholesterol and lipid levels and who are, therefore, at risk for
cardiovascular disease. This is a highly competitive market with multiple
approved products seeking to gain increased market share. Currently, the market
is approximately $13 billion worldwide and experts forecast that the market will
at least double in size by 2005. Identification of genomic markers that would
allow the right drug to reach the right patient would allow a company to boost
its market share and would improve patient compliance, which are both
particularly important factors when maximizing profit from drugs that patients
take over the course of a lifetime.
To gather data for this Mednostics program, we studied approximately
170 individuals who were prescribed one of several cholesterol lowering drugs.
We obtained full medical and family histories and extensive clinical
measurements for these individuals from the Ludwigshafen Risk and Cardiovascular
Health Study in Germany, a large, ongoing longitudinal study being managed by
Dr. Bernard Winkelmann at a teaching hospital of the University of Mainz in
Germany. Doctors have diagnosed these individuals to have conditions such as
coronary artery disease, diabetes, obesity, high cholesterol levels and
hypertension. The drugs used included pravastatin (sold by Bristol-Myers Squibb
Company as Pravachol(R)), atorvastatin (sold by Pfizer Inc. as Lipitor(R)) and
cerivastatin (sold by Bayer AG as Baycol(R)). To date, we have identified HAP
Markers from multiple genes that differentiate how patients respond to a statin.
We are attempting to confirm our findings and are simultaneously approaching a
number of companies which may have an interest in intellectual property we
develop from this Mednostics program.
We do not currently expect to manufacture and market pharmaceutical and
diagnostic products ourselves.
ASTHMA CLINICAL STUDY
To demonstrate how the pharmaceutical industry and healthcare
providers could use our HAP Technology, we conducted a clinical study to
determine a correlation between our HAP Markers or SNPs and an asthma
patient's response to the drug albuterol (sold by Glaxo SmithKline as
Ventolin(R)), a standard treatment for persons with asthma. We conducted the
study in collaboration with Dr. Stephen Liggett, our executive medical
advisor and a professor of medicine at the University of Cincinnati Medical
Center. We initially examined genomic variation in the target of the drug,
the beta2 adrenergic receptor (beta2-AR). We determined the sites of
variation in this gene and then used our DECOGEN informatics system to
organize the SNPs into HAP Markers. We found 13 SNPs in the beta 2-AR gene,
which were organized into only 12 HAP Markers out of a theoretical
possibility of 8,192 (2 to the 13th power) haplotypes. We collapsed the 12
HAP Markers into five major groups using our proprietary methods of
population genomics to increase the likelihood of finding a statistically
relevant correlation.
Dr. Liggett recruited 121 asthmatic individuals for clinical
treatment. Dr. Liggett made a large number of standard pulmonary
measurements, after which he treated the patients with albuterol in a
controlled setting. Approximately 30 minutes after treatment, Dr. Liggett
repeated the pulmonary measurements. The response to the drug differed
significantly from patient to patient and the drug was clinically effective
in only 40% of these patients as measured by generally accepted clinical
criteria. Dr. Liggett and his staff drew blood samples and extracted DNA for
HAP Typing of the beta2-AR receptor gene. We did the HAP Typing and entered
the clinical information and the results from HAP Typing into the DECOGEN
informatics system. The search engine of our DecoGen informatics system
analyzed the data for a correlation between combinations of HAP Markers as
well as individual SNPs and the response to albuterol.
Our DECOGEN informatics system found a correlation between specific
pairs of HAP Markers in the beta 2-AR receptor gene and both a positive response
and a poor response to albuterol. By contrast, no individual SNP correlated with
the
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response to albuterol in this study. This study, which was similar in sample
size used for a phase II clinical trial, showed that a patient's response to
albuterol correlated, in a statistically significant manner, with specific HAP
Markers. We have filed a patent application on the correlation and published a
more detailed description of this study in the Proceedings of the National
Academy of Sciences on September 12, 2000.
OUR TECHNOLOGY
OVERVIEW
Our process for discovering HAP Markers eliminates the need to find and
then test large numbers of families or related individuals to determine genomic
variation. Initially, we discover individual SNPs by high-throughput sequencing
of DNA samples of unrelated and related individuals that are representative of
the individuals who constitute the major pharmaceutical markets of the world. We
use our proprietary algorithms to organize the SNPs into HAP Markers. Using
these algorithms, we find that the number of actual HAP Markers per gene is
significantly less than the theoretically large number of ways in which SNPs
could be organized.
Our DECOGEN informatics system contains a number of components. Our HAP
Database contains our HAP Markers including information about their sequence,
frequency and distribution. Our DECOGEN informatics system also contains a
proprietary collection of algorithms and a search engine that correlates a
patient's HAP Markers with a particular response to a drug. Using our DECOGEN
informatics system, we can determine with statistical accuracy the correlation
between HAP Markers and drug response in a small population of the size commonly
seen in phase I and phase II of a clinical trial.
HAP Typing is our process for measuring which HAP Marker pairs are
present in a patient's DNA sample. Our HAP Typing facility uses proprietary
software, robotics and Sequenom's MassARRAY(TM) platform to determine, on a
high-throughput basis, which two HAP Markers for a gene are present in a
patient's DNA sample. We integrate the resulting data into our DECOGEN
informatics system to search for a correlation with a patient's drug response.
The following outlines the components of our HAP Technology and how we
use our HAP Technology to detect a correlation with a drug response.
[FLOW CHART OUTLINING THE COMPONENTS OF OUR
HAP TECHNOLOGY AND HOW WE USE IT TO DETECT
A CORRELATION WITH A DRUG RESPONSE]
GENE SELECTION
Our goal is to discover HAP Markers for all of the pharmaceutically
relevant genes. We prioritize these genes for HAP Marker discovery based upon
the needs of our HAP2000 partners and our Mednostics programs. We obtain genomic
information relevant for gene selection from publicly available sources, such as
the Human Genome Project, and from proprietary databases. We are discovering HAP
Markers for genes that:
o are, or will likely become, drug targets;
o are associated with drug target pathways;
o are involved in how drugs modify cell communication or regulate other
genes; and
o are involved in the metabolic process by which the body absorbs a drug and
breaks it down.
INDEX REPOSITORY
We use our Index Repository, a collection of diverse DNA samples, to
discover the SNPs that are present in genes. We designed our Index Repository
to:
o contain genomic information that would be representative of the people who
constitute the major pharmaceutical markets of the world;
10
o aid in the quality control analysis of the SNPs we discover; and
o facilitate the organization of SNPs into HAP Markers.
To build our Index Repository, we recruited 200 individuals whose
parents and grandparents came from specified geographical regions. We obtained
personal information from each individual, including sex, date of birth, and
general medical information, as well as a detailed family history and drew blood
samples so that we could create continually multiplying cells from the white
cells present in the blood. The resulting cells, called permanent cell lines,
provide us with a supply of DNA from which to discover SNPs. We store frozen
samples of each cell line at multiple locations to ensure that all of these cell
lines are available in the future. To supply sufficient DNA for the production
process, we routinely grow the cell lines in our cell culture facility. We
employ quality control procedures that permit each DNA sample to be
unambiguously matched to its corresponding cell line. We store all of the
information about a cell line in our proprietary HAP Database that is a
component of our DECOGEN informatics system.
We are adding to the content of our Index Repository and will have at
least 300 additional individuals whose parents and grandparents are from
geographical regions that represent emerging and specialized pharmaceutical
markets. We plan to use this new resource to obtain additional population
variability information for specialized applications.
DISCOVERING SNPS
We use a subset of our Index Repository to discover SNPs. We employed
principles of population statistics to determine the minimum number of unrelated
individuals that we needed to have a 99% probability of detecting a SNP or HAP
Marker that occurs:
o in at least 5% of the general population or
o in at least 10% of a population from a specific geographical region.
We sequence individual samples of DNA so that we can accurately
determine the frequency of a SNP in the population. Our procedure allows us to
detect SNPs that are present at lower frequencies than if we were to analyze a
mixture of DNA from different individuals, as is done by some companies.
We sequence 93 individual, human DNA samples, or 186 individual
genomes, from our Index Repository in the following genomic regions for each
selected gene:
o the region responsible for controlling when a gene is active, the control
region;
o the regions containing coding information that is found in the protein
product of the gene, the coding regions;
o the boundaries between the genomic regions containing coding information
and those interspersed regions that do not contain coding information, the
non-coding regions; and
o the region at the end of a gene immediately after the last region
containing coding information.
The following diagram shows the regions of genomic DNA we sequence.
[DIAGRAM SHOWING REGIONS OF GENOMIC DNA WE SEQUENCE]
Our process of discovering SNPs distinguishes us from other companies.
Some companies sequence cDNA, which is a test tube synthesized product that does
not contain sequence information for some key genomic regions that we sequence.
As a result, these companies cannot detect the SNPs that are present in these
regions. In addition, the DNA we use is easily obtainable from blood samples
whereas tissue biopsies may be necessary to synthesize cDNA products for certain
genes.
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Our sequencing process is highly automated, from picking the regions to
be sequenced through loading the samples onto one of our sequencing machines. We
designed the process in a modular fashion so that we can easily update
procedures with improved technology without the need to shut down the entire
production process. We operate our sequencing facility 24 hours a day, seven
days a week and have 59 ABI Prism(R) 3700 capillary sequencers, manufactured by
Applied Biosystems, a division of Applera Corporation, in operation.
We have also developed a proprietary laboratory information management
system to track genes as they progress through the production pipeline. We use
this system to monitor the overall quality of data we produce to ensure that the
sequencing process is operating according to our established standards. The
sequence information undergoes two forms of quality control analysis. We use
electronic procedures and established population genomic principles to identify
and validate that a SNP exists at a given position.
HAP MARKERS AND HAP DATABASE
Geneticists use the term haplotype to describe how SNPs are organized
on a chromosome. They study the inheritance of genetic variability in extended
families in order to determine haplotypes. Family studies allow a geneticist to
differentiate which of the two copies of a chromosome an individual inherited
from each parent. The haplotype is the standard for describing genetic
variability.
We do not need to conduct family studies to discover haplotypes. Rather
than relying on family studies, we have developed an entirely computerized
process for discovering haplotypes. Our proprietary method works because we
analyze a large number of individual samples and we have members of extended
families in our sample set. We have validated the accuracy of our computerized
process by conventional family studies and molecular techniques. We use our
proprietary computational methods and algorithms to determine how the SNPs in a
gene are organized on each of the two chromosomes in each sample we sequence
from our Index Repository. We use the term HAP Marker, derived from haplotype,
to describe the organization of SNPs we find for a gene. Without our
high-throughput computerized process, the discovery of our HAP Markers would not
be commercially feasible.
Our computerized process assigns a confidence value to each HAP Marker
we discover. If the HAP Markers we discover for a gene fall below a defined
confidence level, we subdivide the gene into regions. We reexamine each region
until we identify HAP Markers that meet our acceptance level. We then enter each
HAP Marker into our proprietary HAP Database. We also enter other relevant
population information, such as the distribution and frequency of each HAP
Marker among people from different geographical regions. We also include in our
HAP Database other genomic markers that others have identified and are available
in public databases.
As of December 30, 2000, we had processed in excess of 3,000
pharmaceutically relevant genes through our production process and deposited
our HAP Markers and associated information into our HAP Database. All of the
nearly 500 current drug targets have gone through our production process. We
will use some of our capacity to sequence certain genes in more than 93
individuals in order to obtain additional population variability information
for specialized applications. We will also use some of our capacity to
sequence genes in specific populations with a defined disease in order to
identify predictive markers for disease susceptibility. To date, we have
found an average of approximately 15 SNPs per gene. There are generally two
possible forms of a SNP that are found at a site of genomic variation.
Therefore, these 15 SNPs could theoretically be organized into 2 to the 15th
power or 32,768 potential HAP Markers. Using our proprietary algorithms, we
found that these SNPs are organized into an average of only approximately 17
HAP Markers per gene.
THE DECOGEN INFORMATICS SYSTEM
We have assembled a team of 65 informatics professionals, 24 of whom
have a Ph.D., to integrate the high information content of our HAP Markers into
the pharmaceutical development and marketing process. This team consists of
individuals with training and experience in software engineering, population
statistics, clinical statistics, workflow systems, and computational molecular
biology. We have constructed a proprietary informatics system, called DECOGEN,
which is short for decoding genes. Our DECOGEN informatics system contains the
proprietary database of population information for our Index Repository and our
proprietary HAP Database of HAP Markers. This database can accommodate
information from a variety of populations, including individuals suffering from
a specific disease and patients in clinical trials, as well as associated data
such as detailed medical histories including responses to drugs. The portal to
the HAP Database is the
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DECOGEN search engine, which we designed with an intuitive, graphical user
interface so that drug development clinicians can easily manage their data to
find a correlation between HAP Markers and a drug response.
We have constructed the graphical interface to display a series of
views that contain information, beginning with a summary and extending down into
details. For example, in each project, we define a set of candidate genes for
use in the clinical study. This collection of genes can generally be organized
into a series of biochemical pathways, which we graphically display in our
DECOGEN informatics system. The user can point and click on any gene in the
pathway and obtain detailed information about that gene. One view provides
information on the structure of a gene and the physical location of the SNPs,
along with the limited number of ways in which these SNPs are organized into HAP
Markers. This view also displays the frequency of each HAP Marker in the
different sub-populations. With another view, a user can see the HAP Markers for
individual patients in a clinical trial alongside of their demographic and
clinical data.
Our DECOGEN informatics system provides more detailed views for experts
in various areas. For example, population genomic data are available at the
click of a mouse. We also provide views that show the statistics behind any
correlation found between HAP Markers and a drug response. Our DECOGEN
informatics system can use either qualitative or quantitative clinical
measurements as a clinical endpoint to search for a correlation with our HAP
Markers. Our DECOGEN informatics system has the ability to exchange information
with standard software packages used in the pharmaceutical industry.
Additional tools are available in our DECOGEN informatics system to
help in the design and operation of clinical trials. To avoid introducing a
bias, clinicians take into account factors such as age and sex when they
randomize patients between the drug and placebo arms of a clinical trial.
Clinicians can use our HAP Markers to compare the genomic background of the
patients in the two arms of a clinical trial. This function allows the clinician
to determine whether the two patient populations were genetically comparable.
Clinicians can also use this function to match patients for assignment to the
two arms of a trial to ensure that the genomic backgrounds are comparable.
Through December 31, 1999, we were developing a prototype of our
DECOGEN informatics system, which did not have all the major functions and was
not ready for initial customer testing. We established technological feasibility
during the first quarter of 2000, when we evolved the prototype into a working
model which expanded the functionality of our DECOGEN informatics system. In
June 2000, we made our DECOGEN informatics system available for initial customer
testing and in July 2000, we placed a test model with a potential customer for
evaluation. On December 4, 2000, we installed a completed version of our DECOGEN
informatics system for our first HAP2000 program partner, Janssen Research
Foundation.
HAP TYPING
We use the term HAP Typing to describe the process of determining which
HAP Marker is present for each of the two versions of each gene in a patient's
clinical sample. The first step in searching for a clinical correlation is to do
HAP Typing on the clinical samples we receive from a HAP2000 partner or obtain
for a Mednostics program. Because of the information content in our HAP Markers,
we can detect a correlation between a HAP Marker and a drug response with
statistical accuracy in a small population, such as is used in phase II clinical
trials. Other companies propose using numerous, unorganized SNPs to detect a
correlation. Our analysis of the genes, which we have examined, demonstrated
that, in general, haplotypes have more predictive power than do individual SNPs.
In addition, our analysis showed that one will obtain a significant number of
spurious correlations if one uses individual, unorganized SNPs. Thus, if
clinicians use individual SNPs as genomic markers, they need a large number of
patients, similar to what pharmaceutical companies generally use in phase III
trials, to find a correlation with similar statistical accuracy.
Our DECOGEN informatics system contains a proprietary computational
tool that facilitates the use of HAP Markers for HAP Typing. Our SNP discovery
process identifies the positions of variation within a gene. Thus, we examine
only these variable positions in a clinical sample. Our proprietary algorithms
determine the minimal number and combination of variable sites, which we must
analyze in order to identify, with high confidence, the two HAP Markers that are
present for each gene in a clinical sample of DNA. This proprietary tool
exploits an established genetic principle. That is, the presence of a given form
of genomic variation at one position can be highly predictive of the form of
genomic variation present at another site in a gene. This predictability reduces
the complexity of the information needed to identify a HAP Marker in a genomic
sample. We can determine this predictability, however, only if we already know
the haplotype or the organization of SNPs in a gene. Our HAP Markers contain
this needed information.
13
We use our HAP Typing capabilities to support our HAP2000 partners and
our Mednostics programs and to obtain additional population information for
certain HAP Markers. We have a customized 8,000 square foot facility, dedicated
to HAP Typing, which we will make compliant with government regulations under
CLIA and have developed proprietary software to track samples through the
facility. We designed this facility to handle initially at least three million
genomic tests per year. We have adopted Sequenom's MassARRAY(TM) high-throughput
technology to do our HAP Typing. We expect additional shifts of technicians and
MassARRAY(TM) systems to increase the capacity to at least 18 million genomic
tests per year. We are developing genomic tests for a number of our HAP Markers
and intend to use these tests for clinical studies with our HAP2000 partners and
for our Mednostics programs.
OUR COLLABORATIONS
To date, we have entered into the following licenses and
collaborations:
JANSSEN RESEARCH FOUNDATION, A JOHNSON & JOHNSON COMPANY
Effective November 22, 2000, we entered into a multi-year collaboration
agreement with Janssen Research Foundation, referred to as JRF, under which we
have granted JRF a license to our HAP Technology. We have installed our DECOGEN
informatics system at The R.W. Johnson Pharmaceutical Research Institute,
referred to as PRI, a member of the Johnson & Johnson family of companies. We
expect to collaborate with JRF and PRI in research projects to identify HAP
Markers associated with a patient's response to their drugs and with disease
susceptibility and progression. The agreement will automatically terminate after
a period of years unless JRF elects to exercise its option to terminate within a
year prior to automatic termination. Either party may terminate the agreement
early if the other party breaches the agreement.
GENE LOGIC
Effective June 28, 2000, we entered into a three-year collaboration
agreement with Gene Logic, Inc., under which we have licensed their gene
expression databases on a non-exclusive, perpetual, royalty-free basis, in
exchange for the payment by us of annual access fees. In addition, Gene Logic
has licensed from us certain of our technology on a non-exclusive, perpetual,
royalty-free basis certain of our SNP data in exchange for their payment to us
of annual access fees. Gene Logic will use our SNP data to indicate, in their
gene expression databases, the amount of genomic variability that we found in
certain genes. We will use their gene expression information to indicate, in our
HAP Database, the expression level that Gene Logic observed for a gene in
different tissues under different circumstances. We will also use their data to
help select genes for analysis in our Mednostics programs. Furthermore, Gene
Logic will analyze for our Mednostics programs the level of gene expression in
various samples which we will provide to them during the term of the agreement.
The agreement will automatically terminate after three years unless we choose to
extend the term. Either party may terminate the agreement early if the other
party breaches the agreement or if either party meets certain criteria.
SEQUENOM
Effective May 28, 2000, we entered into a three-year collaboration
agreement with Sequenom, Inc., under which we have committed to use Sequenom's
MassARRAY(TM) system as our exclusive equipment platform for high-throughput SNP
analysis in our new HAP Typing facility. In return, Sequenom will provide
equipment and supplies, as well as ongoing access to information about new
technology and products in development by Sequenom, so that we can adapt such
new technologies and products for use at our HAP Typing facility in the shortest
possible time. In addition, we have the option to be a test site for these new
technologies and products. The agreement requires us to purchase a minimum
number of MassARRAY(TM) systems and allows for predetermined pricing of
consumables. The agreement will automatically terminate after three years, but
either party may terminate the agreement early if the other party breaches the
agreement or if the terminating party is able to meet certain criteria.
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VISIBLE GENETICS
Effective November 21, 1996, we granted to Visible Genetics, Inc. a
worldwide exclusive license to our patented technology relating to the coupled
amplification and sequencing, or CAS, of DNA for diagnostic use. This technology
is not part of our HAP(TM) Technology. Under the terms of the agreement, Visible
Genetics paid us a one-time licensing fee and continues to pay us royalties
based on global sales of products using the licensed technology. Visible
Genetics incorporated the CAS technology in its TruGene(TM) HIV diagnostic kit
which they designed to perform pharmacogenomic analysis of HIV and to customize
HIV and AIDS therapy for particular patient sub-groups. In March 2000, we
amended the agreement to, among other things, reduce the amount of royalties
payable under the agreement and expand the field of the license to the research
products market. In return for the reduction of royalties and broadening of the
field, Visible Genetics has paid us an additional one-time fee of $2 million.
The term of the agreement extends until the last of the patents covered by the
agreement expires. Either party may terminate the agreement early if the other
party breaches the agreement, and we can terminate the agreement early if
Visible Genetics fails to make any payments.
TELIK
Effective February 11, 1998, we entered into a research collaboration
with Telik, Inc. to collaborate on genomics research into estrogen-related
conditions, such as breast cancer and osteoporosis. We amended this
collaboration in February 1999 to extend the term of the collaboration. Telik's
chemoinformatics technologies were used to identify drug candidates that could
modulate the activity of proteins expressed by genes identified by our HAP(TM)
Markers and that were associated with various estrogen receptors. We jointly own
the compounds or other intellectual property rights arising from the
collaboration. We further amended this collaboration in August 2000 to allow
Telik to market the compounds or other intellectual property rights. We will
share the revenues received from any resulting corporate partnering agreements.
INTELLECTUAL PROPERTY
We are pursuing an active program of intellectual property development
and acquisition. In particular, we have developed a system to rapidly file
patent applications on the discoveries from our HAP(TM) Technology. We rely on
patents, trade secrets, non-disclosure agreements, copyrights and trademarks to
protect our proprietary technologies and information. In addition, we are
actively pursuing licensing to third parties our intellectual property that is
peripheral to our core products and services.
We focus our intellectual property strategy on several key areas:
o fundamental methods for conducting our genomics and informatics business;
o HAP(TM) Markers defining the genomic variation discovered in human
populations as well as the genes embodying the HAP Markers;
o HAP(TM) Markers correlated to a drug response or disease susceptibility;
o the HAP(TM) Maker Database and other components of the
DECOGEN(TM) informatics system;
o other proprietary informatics systems for storing and analyzing genomic
variation data; and o novel business methods that utilize our technologies
for providing genomic services to the pharmaceutical and biotechnology
industry.
As of December 30, 2000, our patent portfolio included a total of
four issued and numerous pending patent applications, which we own or for
which we are the exclusive licensee. We have received a U.S. patent, which
covers collecting and analyzing genes from both chromosomes from multiple
individuals in different sub-populations. We have pending patent applications
which cover HAP(TM) Markers for various genes. To protect and extend our
proprietary position in population genomics, we are pursuing patent
protection for all correlations that we identify between our HAP(TM) Markers
and a drug response or susceptibility to a disease. We have also filed patent
applications for components of our DECOGEN(TM) informatics system, including
the process for assembling HAP(TM) Markers
15
and for determining clinical associations. We are pursuing both composition of
matter and method-of-use claims. Our goal is to file patent applications in the
U.S. and abroad on HAP(TM) Markers for every pharmaceutically relevant gene.
We also rely upon unpatented trade secrets and improvements, unpatented
know-how and continuing technological innovation to develop and maintain our
competitive position. We generally protect this information with reasonable
security measures, including confidentiality agreements that provide that all
confidential information developed or made known to others during the course of
the employment, consulting or business relationship shall be kept confidential
except in specified circumstances. Agreements with employees provide that all
inventions conceived by the individual while employed by us are our exclusive
property.
COMPETITION
There is significant competition among entities attempting to use
genomic variation data and informatics tools to develop and market new and
existing medicines. We expect the intensity of the competition to increase. We
face, and will continue to face, competition from pharmaceutical, biotechnology
and diagnostic companies, both in the United States and abroad. Several entities
are attempting to identify and assemble SNP databases. These databases are based
on various technologies and approaches, including the sequencing of either cDNA
or genomic DNA and a genome-wide approach or a candidate gene approach. Some of
these entities are now advocating the use of haplotypes as a measure of genomic
variation. In addition, some of these entities are providing or intend to
provide informatics tools for integrating the use of SNPs into the drug
development process. These entities include, among others, Celera Genomics
Group, Incyte Genomics, Inc. and Variagenics, Inc. In addition, numerous
pharmaceutical companies are developing internal capabilities for identifying
and utilizing gene variation data. In order to compete successfully against
existing and future entities, we must demonstrate the value of our HAP(TM)
Technology and that our informatics technologies and capabilities are superior
to those of our competitors. Many of our competitors have greater resources,
gene variation discovery capabilities and informatics development capabilities
than we do. Therefore, our competitors may succeed in identifying gene variation
and applying for patent protection more rapidly than we do.
We expect that our ability to compete will be based on a number of
factors, including:
o the speed with which we can identify HAP Markers and develop the next
generation of our DecoGen informatics system;
o our ability and the ability of our partners to develop and commercialize
therapeutic and diagnostic products based upon our HAP Technology;
o our ability to attract partners;
o our ability to attract and retain qualified personnel;
o our ability to obtain patent protection; and
o our ability to secure sufficient resources to fund our technology
development and Mednostics programs.
GOVERNMENT REGULATION
Regulation by governmental entities in the United States and other
countries will be a significant factor in the development, manufacturing and
marketing of any product that we or our partners develop. Various federal and,
in some cases, state statutes and regulations govern or influence the
manufacturing, safety, labeling, storage, record keeping and marketing of human
therapeutic and diagnostic products. The extent to which these regulations may
apply to us or our partners will vary depending on the nature of the product.
The FDA does not require companies seeking product approvals to provide data
regarding the correlation between therapeutic response and genomic variation.
Virtually all of the pharmaceutical products developed by our partners
will require regulatory approval by governmental agencies prior to
commercialization. In particular, the FDA in the United States and similar
health authorities in foreign countries will impose on these products an
extensive regulatory review process before they can be marketed. This
16
regulatory process typically involves, among other requirements, preclinical
studies, clinical trials, and often post-marketing surveillance of each
compound. This process can take many years and requires the expenditure of
substantial resources. Delays in obtaining marketing clearance could delay the
commercialization of any therapeutic or diagnostic products developed by our
partners, impose costly procedures on our partners' activities, diminish any
competitive advantages that our partners may attain and lessen our potential
royalties. Any products we or our partners develop may not receive regulatory
approval in a timely fashion or at all.
The FDA regulates human therapeutic and diagnostic products in one of
three broad categories: drugs, biologics, or medical devices. Products developed
using our technologies could potentially fall into any of these three
categories.
The FDA generally requires the following steps for pre-market approval
of a new drug or biological product:
o preclinical laboratory and animal tests;
o submission to the FDA of an investigational new drug application, which
must become effective before clinical trials may begin;
o adequate and well-controlled human clinical trials to establish the safety
and efficacy of the product for its intended indication;
o submission to the FDA of a new drug application, or NDA, if the FDA
classifies the product as a new drug, or a biological license application,
or BLA, if the FDA classifies the product as a biologic; and
o FDA review of the NDA or BLA in order to determine, among other things,
whether the product is safe and effective for its intended uses.
The FDA classifies medical devices, which include diagnostic products,
as class I, class II or class III, depending on the nature of the medical device
and the existence in the market of any similar devices. Class I medical devices
are subject to general controls, including labeling, premarket notification and
good manufacturing practice requirements. Class II medical devices are subject
to general and special controls, including performance standards, postmarket
surveillance, patient registries and FDA guidelines. Class III medical devices
are those which must receive premarket approval, or PMA, by the FDA to ensure
their safety and effectiveness, typically including life-sustaining,
life-supporting, or implantable devices or new devices which have been found not
to be substantially equivalent to currently marketed medical devices. It is
impossible to say at this time which of these categories will apply to any
diagnostic product incorporating our technologies.
Before a new device can be introduced into the U.S. market, it must, in
most cases, receive either premarket notification clearance under section 510(k)
of the Food, Drug, and Cosmetic Act or approval pursuant to the more costly and
time-consuming PMA process. A PMA application must be supported by valid
scientific evidence to demonstrate the safety and effectiveness of the device,
typically including the results of clinical trials, bench tests, laboratory and
animal studies. A 510(k) clearance will be granted if the submitted information
establishes that the proposed device is "substantially equivalent" to a legally
marketed class I or class II medical device or a class III medical device for
which the FDA has not called for PMAs. While less expensive and time-consuming
than obtaining PMA clearance, securing 510(k) clearance may involve the
submission of a substantial volume of data, including clinical data, and may
require a lengthy substantive review.
Even if regulatory clearance is obtained, a marketed product and its
manufacturer are both subject to continuing review. Discovery of previously
unknown problems with a product may result in withdrawal of the product from the
market, which could reduce our revenue sources and hurt our financial results.
Violations of regulatory requirements at any stage during the process, including
preclinical studies and clinical trials, the review process, post-marketing
approval or in manufacturing practices or manufacturing requirements, may result
in various adverse consequences to us, including:
o the FDA's delay in granting marketing clearance or refusal to grant
marketing clearance of a product;
o withdrawal of a product from the market; or
o the imposition of civil or criminal penalties against the manufacturer and
holder of the marketing clearance.
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Generally, similar regulatory requirements apply to products intended
for marketing outside the United States.
We use clinical samples of blood from individuals in developing our
Index Repository and in our Mednostics programs. On our own or in conjunction
with a Contract Research Organization or a Contract Laboratory Organization,
with which we have a contract, we collect these blood samples, plus personal and
medical information about each individual. Similarly, we prepare the sample
collection protocol and the patient informed consent form. The individual
clinical sites recruit the patients for each clinical study and, following the
study protocol, explain and obtain the signed and witnessed informed consent
documents from each patient. The informed consent form includes the patient's
authorization to use the patient's blood sample and data derived from it for
developing commercial products. Independent institutional review boards must
approve the study protocol and the patient informed consent form. We do not
directly identify any of the individuals from whom we receive clinical samples.
We believe that these procedures comply with all applicable federal, state, and
institutional regulations.
HUMAN RESOURCES
As of March 16, 2001, we had 172 full-time employees, 121 of whom were
engaged in research and development activities, 12 of whom were engaged in
clinical development activities and 39 of whom conducted general and
administrative functions. Of the 121 employees engaged in research and
development, 67 were engaged in informatics and 54 were engaged in industrial
genomics. Forty-eight of our employees hold Ph.D. or M.D. degrees, and
thirty-two hold other advanced degrees.
None of our employees are covered by a collective bargaining agreement,
and we consider our relations with our employees to be good.
TRADEMARKS
This report contains our trademarks, Genaissance(R), HAP(TM) Marker,
HAP(TM) Typing, HAP2000(TM) partnership program, HAP(TM) Technology,
DecoGen(TM) informatics system, and Mednostics(TM) program. Each trademark,
trade name or service mark of any other company appearing in this prospectus
belongs to its holder.
ITEM 1A. EXECUTIVE OFFICERS
Set forth below is certain information regarding our current executive
officers, including their respective ages as of March 19, 2001:
NAME AGE POSITION
- ---- --- ----------
Gualberto Ruano, M.D., Ph.D................... 41 Chief Executive Officer and Director
Kevin Rakin................................... 40 President, Chief Financial Officer and Director
Kenneth B. Kashkin, M.D....................... 50 Executive Vice President, Chief Medical Officer
Gerald F. Vovis, Ph.D......................... 58 Senior Vice President, Chief Technology Officer
Richard S. Judson, Ph.D....................... 42 Senior Vice President of Informatics
GUALBERTO RUANO, M.D., PH.D. Dr. Ruano cofounded Genaissance and has
served as Chief Executive Officer and Director since 1997. Prior to founding
Genaissance, Dr. Ruano was engaged in research at Yale University where he
focused on haplotyping technologies for profiling genome diversity stemming from
population and evolutionary genetics. Dr. Ruano holds a B.A. degree in
biophysics from The Johns Hopkins University and a M.D. and a Ph.D. in
population genetics from Yale University, where he was a fellow of the Medical
Scientist Training Program and the Ford Foundation.
KEVIN RAKIN. Mr. Rakin cofounded Genaissance and has served as
Executive Vice President, Chief Financial Officer and Director since 1997 and as
of October 2000 has been our President. Prior to 1998, Mr. Rakin was also a
18
Principal at the Stevenson Group, a consulting firm, where he provided financial
and strategic planning services to high-growth technology companies and venture
capital firms. Prior to this, Mr. Rakin was a manager with Ernst & Young's
entrepreneurial services group. Mr. Rakin holds a B.S. in business and a M.S.
degree in finance from the University of Cape Town and a M.B.A. from Columbia
University. He is a chartered accountant.
KENNETH B. KASHKIN, M.D. Dr. Kashkin has been our Chief Medical Officer
and Executive Vice President since September 2000. From 1997 to 2000, he served
as Vice President, Clinical Development at Knoll Pharmaceutical Company. From
1992 to 1997, Dr. Kashkin was at Abbott Laboratories, initially as Venture Head,
Neurosciences and then as Director, Pharmaceutical Ventures. In 1992, he was
Medical Director at Nova Pharmaceutical Corporation. From 1990 to 1992, Dr.
Kashkin was Associate Director, Central Nervous System Clinical Research at
Bayer AG. From 1987 to 1992, he was on the faculty of the Yale University School
of Medicine. Dr. Kashkin has led drug development operations in cardiovascular,
immunology, endocrinology, oncology and central nervous system research. He is
Board Certified in Internal Medicine and Neurology/Psychiatry. Dr. Kashkin holds
a B.A. in history and a M.D. from the University of California at Los Angeles.
GERALD F. VOVIS, PH.D. Dr. Vovis has been our Senior Vice President of
Genomics since April 1999 and as of October 2000 has been our Chief Technology
Officer. From 1980 to 1999, Dr. Vovis was affiliated with Genome Therapeutics
Corporation, a genomics company, most recently as Senior Vice President of
Scientific Affairs. He has twenty years of experience in the management of
genetic research and in the development and management of collaborative research
programs with pharmaceutical and biotechnology companies. Dr. Vovis holds a B.A.
in chemistry from Knox College and a Ph.D. in molecular biology from Case
Western Reserve University.
RICHARD S. JUDSON, PH.D. Dr. Judson has been our Senior Vice President
of Informatics since April 2000 and our Vice President of Informatics since
November 1999. He joined Genaissance in February 1999 as Associate Director,
Bioinformatics. From January 1997 to February 1999, he served as Group Leader in
the Bioinformatics Department of CuraGen Corporation, a genomics company, where
he was responsible for developing software for protein-protein interactions and
DNA sequence analysis. From January 1990 to December 1996, he served as Senior
Member of the Technology Staff at Sandia National Laboratories, leading modeling
projects in several areas including computational drug design, protein modeling
and sequence analysis. Dr. Judson holds a B.A. in chemistry and physics from
Rice University and a M.A. and a Ph.D. in chemistry from Princeton University.
ITEM 2. PROPERTIES
Our executive offices and laboratories are located at Five Science
Park, New Haven, Connecticut. We lease nearly 67,000 square feet of space, under
a lease expiring on February 28, 2004, which we may extend for 10 years. We have
a right of first refusal on an additional 4,000 square feet within the same
building complex and 24,000 square feet in an adjacent building.
ITEM 3. LEGAL PROCEEDINGS
We are not a party to any material legal proceedings.
ITEM 4. SUBMISSION OF MATTERS TO A VOTE OF SECURITY HOLDERS
No matters were submitted to stockholders for a vote during the fourth
quarter of 2000.
19
PART II
ITEM 5. MARKET FOR THE REGISTRANT'S COMMON STOCK AND RELATED STOCKHOLDER
MATTERS
Our common stock is currently quoted on the Nasdaq National Market
under the symbol "GNSC."
Our common stock began trading on August 2, 2000 and the high and
low closing sale prices as reported by Nasdaq were as follows:
HIGH LOW
2000
Third Quarter........................... $ 23.50 $ 13.25
Fourth Quarter.......................... $ 33.3124 $ 10.50
As of March 27, 2001, there were approximately 328 holders of record of
our common stock and approximately 4,978 beneficial owners of common stock.
We have never paid cash dividends on our common stock and we do not
anticipate paying any cash dividends in the foreseeable future. We currently
intend to retain future earnings, if any, for use in our business.
In February 2000 we issued 636,364 shares of series B convertible
preferred stock upon the conversion of convertible promissory notes we issued in
the aggregate amount of $3,500,000 in November 1999. In connection with these
convertible promissory notes, we issued warrants to purchase 12,727 shares of
common stock at an exercise price of $5.50. During the first quarter of 2000, we
issued 7,900 shares of common stock for an aggregate sale price of $23,700,
issued warrants to purchase 48,454 shares of common stock at exercise prices
ranging from $4.00 to $8.25 per share and granted options to purchase 73,000
shares of common stock at exercise prices ranging from $4.00 to $5.50 per share.
In February and March 2000, we completed a private placement offering of
7,907,160 shares of series B convertible preferred stock and 183,749 shares of
Series KBH nonvoting convertible preferred stock (exclusive of the 636,364
shares of common stock issued in connection with the conversion of the
$3,500,000 promissory notes) for an aggregate sale price of $44,500,000. In
March 2000, we completed a private placement offering of 1,539,393 shares of
series C convertible preferred stock, for an aggregate sale price of
$12,699,992.
All of the above sales of shares were made in reliance on the exemption
from registration under Section 4(2) of the Securities Act of 1933, as amended,
as transactions not involving a public offering and Rule 701 under the
Securities Act of 1933, as amended, as some of the issuances were to employees
and consultants as compensation. We retained Legg Mason Wood Walker, Inc. as
placement agent in connection with the February and March 2000 private
placements, who received aggregate compensation of $2.5 million, including
$67,826 of expenses and a common stock purchase warrant for 400,000 shares
exercisable at $6.05 per share for their services. There were no underwriters
employed in connection with any of the other transactions set forth above.
During the three months ended December 31, 2000, individuals exercised
options to purchase an aggregate of 39,800 shares of our common stock for an
aggregate purchase price of $48,500. These issuances were made in reliance upon
Rule 701 under the Securities Act of 1933, as amended.
On August 1, 2000, the Securities and Exchange Commission declared our
Registration Statement on Form S-1 (File No. 333-35314) effective in connection
with the initial public offering of our common stock. Deutsche Banc Alex. Brown,
Bear, Stearns & Co. Inc., Salomon Smith Barney and UBS Warburg LLC served as
managing underwriters of the offering.
On August 7, 2000, we sold 6,000,000 shares of our common stock
(excluding the underwriters' overallotment option) at $13.00 per share to the
underwriters. We received net proceeds in the initial public offering of
approximately $71,100,000, reflecting gross proceeds of $78,000,000, net of
underwriting discounts and commissions of approximately $5,460,000 and other
offering costs of approximately $1.4 million.
On August 31, 2000, we sold 900,000 shares of our common stock (in
connection with the exercise of the underwriters' overallotment option) at
$13.00 per share to the underwriters. We received net proceeds of approximately
$10,881,000, reflecting gross proceeds of $11,700,000, net of underwriting
discounts of approximately $819,000.
The proceeds from our initial public offering have been invested in
interest-bearing high-grade corporate bonds and money market accounts.
20
ITEM 6. SELECTED FINANCIAL DATA
The following selected financial data should be read in conjunction
with our financial statements and related notes and "Management's Discussion and
Analysis of Financial Condition and Results of Operations" appearing elsewhere
in this Annual Report on Form 10-K. The selected balance sheet data set forth
below, as of December 31, 1999 and 2000 and the statements of operations data
for each of the years in the three-year period ended December 31, 2000, are
derived from our financial statements which have been audited by Arthur Andersen
LLP, independent public accountants and are included elsewhere in this Annual
Report on Form 10-K. The selected balance sheet data as of December 31, 1996,
1997 and 1998 and selected statements of operations data for the years ended
December 31, 1996 and 1997 are derived from audited financial statements not
included in this Annual Report on Form 10-K. The historical results are not
necessarily indicative of the results we expect for future periods. This data is
in thousands, except per share data.
YEAR ENDED DECEMBER 31,
-----------------------------------------------------
1996 1997 1998 1999 2000
STATEMENT OF OPERATIONS DATA:
Revenues............................ $ 1,141 $ 1,505 $ 1,343 $ 680 $ 753
Operating expenses:
Research and development(1)....... 1,010 1,643 3,017 6,259 25,680
General and administrative(1)..... 304 415 894 2,714 8,837
Sublicense royalty obligations.... 93 19 68 20 530
Deferred stock compensation....... 685 106 473 766 5,256
--------- --------- --------- --------- ---------
Total operating expenses............ 2,092 2,183 4,452 9,759 40,303
--------- --------- --------- --------- ---------
Loss from operations................ (951) (678) (3,109) (9,079) (39,550)
Interest income (expense), net...... (78) (125) (30) (370) 2,784
Realized gains on investments....... -- -- 259 -- --
--------- --------- --------- --------- ---------
Net loss............................ (1,029) (803) (2,880) (9,449) (36,766)
Preferred stock dividends and
accretion........................ -- -- (741) (2,082) (6,327)
Beneficial conversion feature of
Series B, KBH and C preferred
stock............................ -- -- -- -- (50,180)
--------- --------- --------- --------- ----------
Net loss attributable to common
shareholders..................... $ (1,029) $ (803) $ (3,621) $ (11,531) $ (93,273)
========= ========= ========= ========= ==========
Net loss per common share, basic
and diluted...................... $ (0.47) $ (0.40) $ (1.67) $ (4.24) $ (8.55)
========== ========== ========== ========== ==========
Weighted average shares used in
computing net loss per common
share, basic and diluted......... 2,207 1,983 2,165 2,719 10,908
========== ========== ========== ========== ==========
Pro forma net loss per common
share, basic and diluted......... $ (.76) $ (1.79) $ (5.16)
========== ========== ==========
Pro forma weighted average shares
used in computing net loss per
common share, basic and diluted.. 3,807 5,202 16,790
========== =========== ==========
- ------------------
(1) Excludes non-cash, stock
based compensation expense as
follows:
Research and development...... $ 219 $ 64 $ 427 $ 499 $ 1,694
Selling, general and
administrative.............. 466 42 46 267 3,562
--------- --------- --------- --------- ----------
$ 685 $ 106 $ 473 $ 766 $ 5,256
========= ========= ========= ========= ==========
21
DECEMBER 31,
1996 1997 1998 1999 2000
------- -------- -------- --------- ----------
BALANCE SHEET DATA:
Cash, cash equivalents and investments.. $ 304 $ 1,420 $ 7,419 $ 3,666 $ 110,376
Total assets............................ 782 1,899 8,946 11,514 143,892
Long-term liabilities................... 1,113 1,405 2,869 11,407 24,305
Redeemable convertible preferred stock.. -- 750 9,945 11,247 --
Accumulated deficit..................... (3,645) (4,501) (8,122) (19,654) (112,927)
Total stockholders' equity (deficit).... (822) (1,369) (4,624) (14,832) 105,675
22
ITEM 7. MANAGEMENT'S DISCUSSION AND ANALYSIS OF FINANCIAL CONDITION AND RESULTS
OF OPERATIONS
THE FOLLOWING DISCUSSION AND ANALYSIS OF OUR FINANCIAL CONDITION AND
THE RESULTS OF OPERATIONS SHOULD BE READ IN CONJUNCTION WITH "SELECTED FINANCIAL
DATA" AND OUR FINANCIAL STATEMENTS AND RELATED NOTES APPEARING ELSEWHERE IN THIS
REPORT.
OVERVIEW
Since our inception, we have incurred significant operating losses,
and, as of December 31, 2000, we had an accumulated deficit of $112.9 million.
The majority of our operating losses have resulted from costs we incurred
developing our HAP Technology and initiating our Mednostics programs, and we
expect to dedicate a significant portion of our resources for the foreseeable
future to further develop and maintain our HAP Technology, expand our Mednostics
programs and intensify our commercialization activities. To date, our revenues
have been primarily from licensing fees from our agreements with Janssen
Research Foundation and Gene Logic, Inc., as well as a sublicensing agreement
with Visible Genetics, Inc. and government grants. We expect that it will be
several years, if ever, before we generate significant revenues.
RESULTS OF OPERATIONS
YEARS ENDED DECEMBER 31, 2000 AND 1999
Revenue consists primarily of proceeds received in connection with the
licensing of our HAP Technology, sublicensing of patents and research grants.
Revenue increased to $753,000 in 2000 from $680,000 in 1999. The increase in
revenues is due to a $555,000 increase in license fees from 1999 to 2000, offset
by a $557,000 decrease in grant research revenue. The increase in license
revenues is attributable to the commercialization of our HAP 2000 program and
agreements entered into during 2000 with Janssen Research Foundation and Gene
Logic, Inc. We are recognizing the annual license and subscription fees over the
term of the agreements and the service fees as the services are performed.
Future milestone and royalty payments, when and if received, will be recognized
when earned. Revenue in 2000 also includes the amortization, over the remaining
life of the sublicensed patent, of upfront payments received in connection with
the sublicensing of a patent. The decrease in grant research revenue occurred
because we decided not to pursue research grant funding but to focus instead on
commercializing our HAP Technology.
Research and development expenses consist primarily of payroll and
benefits for research and development personnel, materials and reagent costs,
depreciation and maintenance costs for equipment used for HAP Marker discovery
and facility related costs. Research and development costs increased to $25.7
million in 2000 from $6.3 million in 1999. The increase in expenditures is
primarily attributable to the significant increase in the discovery of HAP
Markers during 2000, the initiation of our HAP Typing facility, the increase in
informatics personnel focused on improvements to our proprietary DecoGen
informatics system, the costs of preparing to launch our first Mednostics
clinical trial and an increase in patent personnel and patent applications. The
increase in expenses includes a $6.6 million increase in laboratory supplies, a
$5.7 million increase in payroll and related costs and a $2.5 million increase
in depreciation expense. We expect research and development costs to continue to
increase significantly over the next few years as we continue to expand our
Mednostics clinical studies, increase our database of HAP Markers, increase the
use of our HAP Typing facility, prosecute our patent applications, and continue
to invest in ongoing product development and improvements related to our DecoGen
informatics system.
Selling, general and administrative expenses consist primarily of
salary and related costs for executive, business development, finance, public
affairs and other administrative personnel as well as facility related costs and
outside professional fees incurred in connection with corporate development,
general legal and financial matters. Selling, general and administrative
expenses increased to approximately $8.8 million in 2000 from $2.7 million in
1999. The increase is primarily attributable to a $2.6 million increase in
payroll and related costs and a $1.0 million increase in professional fees. We
expect selling, general and administrative costs to continue to increase over
the next few years to support our growth, to expand our business development,
marketing and commercialization efforts and to pay the cost of operating as a
public company.
23
Sublicensing royalty expense represents royalties incurred by us on
sublicensing fees received. The increase in sublicensing royalty expense to
$530,000 from $20,000 in 1999 relates primarily to a nonrefundable cash payment
received in 2000 in connection with an amendment to the patent sublicensing
agreement. We have elected to recognize this expense as incurred.
Stock based and other non-cash compensation expense relates to options
granted to employees, options granted to scientific advisory board members and a
sale of stock in exchange for a note, between two of our officers and a major
shareholder. The accounting for options granted to employees is accounted for in
accordance with APB No. 25. The accounting for scientific advisory board members
requires us to record periodic charges for unvested options based on an increase
in the fair value of our common stock and the related vesting of the options.
The accounting for the stock sale between our officers and a major shareholder
required us to record periodic charges, through the date of the initial public
offering, based on an increase in the fair value of our common stock to
recognize the benefit obtained by us as a result of the stock sale. Stock based
compensation increased to $5.3 million in 2000 from $766,000 in 1999. The
increase is primarily due to our decision to vest fully all unvested options
previously granted to scientific advisory board members in March 2000, which
resulted in a one-time expense of approximately $1.4 million, as well as the
recording of approximately $2.9 million of expense related to the officer stock
purchase agreement due to the increase in the fair value of the stock through
the date of our initial public offering. Future unamortized compensation expense
associated with outstanding stock options at December 31, 2000 is approximately
$1.1 million.
Interest income increased to approximately $4.6 million in 2000 from
$267,000 in 1999. The increase is the result of our investment of the proceeds
raised in connection with our issuance of preferred stock in February and March
2000 and our initial public offering in August 2000.
Interest expense increased to approximately $1.8 million in 2000 from
$637,000 in 1999. The increase is due primarily to additional capital lease and
other debt obligations. During 2000, we borrowed $18.7 million under capital
lease arrangements to fund the acquisition of equipment to significantly expand
our HAP Marker discovery and HAP Typing capacity. In addition, we borrowed
approximately $3.9 million to partially fund the expansion of our facilities.
YEARS ENDED DECEMBER 31, 1999 AND 1998
Revenue decreased to $680,000 in 1999 from $1.3 million in 1998. The
decrease resulted primarily from a $649,000 decrease in grant research revenue.
The decrease in grant research revenue occurred because we decided not to pursue
research grant funding.
Research and development expenses increased to $6.3 million in 1999
from $3.0 million in 1998. The increase was attributable to the increased
production of HAP Markers and the development of our proprietary DECOGEN
informatics system.
Selling, general and administrative expenses increased to $2.7 million
in 1999 from $894,000 in 1998. The increase was attributable to an increase in
personnel from our expanded operations, additional business development costs
from marketing our products, and higher operating costs from our move to a
larger facility in February 1999.
Stock based compensation expense increased to $777,000 in 1999 from
$473,000 in 1998 due to an increase in the fair value of our common stock
applied to the additional vesting of options and the stock sale between two of
our officers and a major shareholder.
Interest income increased to $267,000 in 1999 from $88,000 in 1998. The
increase was due to proceeds received in connection with the issuance of
preferred stock in August of 1998, which resulted in an increase in funds
available for investment.
Interest expense increased to $637,000 in 1999 from $118,000 in 1998.
The increase was due primarily to additional capital lease and other debt
obligations.
Realized gains on investments in 1998 resulted from the one-time sale
of an investment in common stock that was acquired by us in 1996.
24
LIQUIDITY AND CAPITAL RESOURCES
We have financed our operations primarily through the private sale
of common and preferred stock, government research grants, payments under
licensing agreements, loans and capital leases. From inception through
December 31, 2000, we have received aggregate gross proceeds of approximately
$162.8 million from issuance of common and preferred stock. In addition,
through December 31, 2000, we had received $4.5 million of government grant
funding and $4.4 million from license fees, royalties and research contracts.
We also have received $24.4 million from capital lease financing and $7.8
million from other loans. The proceeds from capital lease financing and other
loans have been used to acquire $35.6 million of property and equipment. On
December 31, 2000, we had available borrowing capacity of $1.1 million under
capital lease agreements and $366,000 under long-term loans for facility
improvement costs. We are using the $1.1 million available under capital
lease agreements to finance equipment purchases. It is our intention to
continue to expand production and office facilities and to acquire
state-of-the art equipment to continue the discovery of HAP Markers for all
pharmaceutically relevant genes and increase the throughput of our HAP Typing
facility.
Cash used in operations for the year ended December 31, 2000 was $21.3
million compared with $7.4 million for the same period in 1999. A net loss of
$36.8 million in 2000 was partially offset by non-cash charges of $4.9 million
for stock based compensation expense and $4.1 million for depreciation and
amortization expense, as well as increases of $4.4, $1.6 and $1.9 million in
accounts payable accrued expenses and deferred revenue, respectively.
Cash used for investing activities was $49.8 million in 2000 compared
with cash provided by investing activities of $2.2 million in 1999. In 2000, we
used cash to purchase $8.7 million of property and equipment and invested $41.1
million in marketable securities.
Cash provided by financing activities was $136.6 million in 2000
compared to $4.7 million in 1999. We received net proceeds of $136.7 million
through issuance of preferred and common stock during 2000.
On December 31, 2000, cash, cash equivalents and short-term investments
totaled $110.4 million compared to approximately $3.7 million at December 31,
1999. Our cash reserves are held in interest-bearing high-grade corporate bonds
and money market accounts. In August 2000, we completed the initial public
offering of 6,900,000 shares of common stock at a price of $13.00 per share, for
net proceeds of $82.0 million. We believe that our existing cash reserves, the
proceeds from our initial public offering, and our available borrowing capacity
will be sufficient to support our planned operations for at least 24 months.
Our cash requirements will vary depending upon a number of factors,
many of which are beyond our control, including:
o the demand for our HAP Technology;
o the efforts and success of our HAP2000 partnership program;
o the number of Mednostics programs we commence;
o the results and commercialization of our Mednostics programs;
o the level of competition we face;
o our ability to develop, market and license new technology; and
o our ability to effectively manage operating expenses.
INCOME TAXES
We have not generated any taxable income to date and, therefore, have
not paid any federal income taxes since inception. On December 31, 2000, we had
available unused net operating loss carryforwards of approximately $43.3 million
and $42.9 million which may be available to offset future federal and state
taxable income, respectively. Use of
25
our federal and state net operating loss carryforwards, which will begin to
expire in 2007 and 2001, respectively, may be subject to limitations. The future
utilization of these carryforwards may be limited due to changes within our
current and future ownership structure as defined within the income tax code. We
have recorded a full valuation allowance against our deferred tax asset, which
consists primarily of net operating loss carryforwards, because of uncertainty
regarding its recoverability, as required by Financial Accounting Standard No.
109 "Accounting for Income Taxes."
RECENT ACCOUNTING PRONOUNCEMENTS
In December 1999, Staff Accounting Bulletin No. 101 (SAB 101), "Revenue
Recognition," was issued. The revenues included in the accompanying statements
of operations, for all periods presented, are in accordance with the provisions
of SAB 101.
In June 1998, the Financial Accounting Standards Board issued SFAS No.
133, "Accounting for Derivative Financial Instruments and for Hedging
Activities" (SFAS No. 133) which provides a comprehensive and consistent
standard for the recognition and measurement of derivatives and hedging
activities. SFAS No. 133 is effective for fiscal years beginning after January
1, 2001. We do not believe that the adoption of SFAS No. 133 will have an impact
on our results of operations or financial condition as we hold no derivative
financial instruments and we do not engage in hedging activities.
FACTORS AFFECTING FUTURE OPERATING RESULTS
Our future operating results could differ materially from the results
described above due to the risks and uncertainties described in exhibit 99.1 to
this Annual Report on Form 10-K.
ITEM 7A. QUANTITATIVE AND QUALITATIVE DISCLOSURES ABOUT MARKET RISK
Our exposure to market risk is principally confined to our cash equivalents and
investments, all of which have maturities of less than 18 months. We maintain a
non-trading investment portfolio of investment grade, liquid debt securities
that limit the amount of credit exposure to any one issue, issuer or type of
instrument. The weighted average interest rate on marketable securities at
December 31, 2000, was approximately 6.72%. In view of the nature and mix of our
total portfolio, a 10% movement in market interest rates would not have a
significant impact on the total value of our investment portfolio as of December
31, 2000.
On December 31, 2000, we had aggregate fixed rate debt of approximately $27.1
million, including borrowings outstanding under term loans and capital lease
obligations. The weighted average interest rate on this debt at December 31,
2000, was approximately 9.5%. A 10% change in this interest rate would cause a
corresponding increase in our annual expense of approximately $260,000.
26
ITEM 8. CONSOLIDATED FINANCIAL STATEMENTS AND SUPPLEMENTARY DATA
INDEX TO CONSOLIDATED FINANCIAL STATEMENTS
PAGE
REPORT OF INDEPENDENT PUBLIC ACCOUNTANTS 29
FINANCIAL STATEMENTS
Balance Sheets as of December 31, 2000 and 1999 30
Statements of Operations for the Years Ended December 31, 2000, 1999, and 1998 32
Statements of Stockholders' Equity and Comprehensive Loss for the Years
Ended December 31, 2000, 1999, and 1998 34
Statements of Cash Flows for the Years Ended December 31, 2000, 1999 and 1998 35
NOTES TO FINANCIAL STATEMENTS 36
27
REPORT OF INDEPENDENT PUBLIC ACCOUNTANTS
To the Board of Directors and Stockholders of Genaissance Pharmaceuticals, Inc.:
We have audited the accompanying balance sheets of Genaissance Pharmaceuticals,
Inc. (a Delaware corporation) as of December 31, 2000 and 1999, and the related
statements of operations, stockholders' equity and comprehensive loss and cash
flows for each of the three years in the period ended December 31, 2000. These
financial statements are the responsibility of the Company's management. Our
responsibility is to express an opinion on these financial statements based on
our audits.
We conducted our audits in accordance with auditing standards generally accepted
in the United States. Those standards require that we plan and perform the audit
to obtain reasonable assurance about whether the financial statements are free
of material misstatement. An audit includes examining, on a test basis, evidence
supporting the amounts and disclosures in the financial statements. An audit
also includes assessing the accounting principles used and significant estimates
made by management, as well as evaluating the overall financial statement
presentation. We believe that our audits provide a reasonable basis for our
opinion.
In our opinion, the financial statements referred to above present fairly, in
all material respects, the financial position of Genaissance Pharmaceuticals,
Inc. as of December 31, 2000 and 1999, and the results of its operations and its
cash flows for each of the three years in the period ended December 31, 2000 in
conformity with accounting principles generally accepted in the United States.
/s/ Arthur Andersen LLP
Hartford, Connecticut
February 14, 2001
28
GENAISSANCE PHARMACEUTICALS, INC.
Balance Sheets
(Amounts in thousands, except per share data)
DECEMBER 31,
2000 1999
ASSETS
CURRENT ASSETS:
Cash and cash equivalents $ 69,204 $ 3,666
Marketable securities 41,172 --
Accounts receivable 238 --
Other current assets 1,421 206
------------- -------------
Total current assets 112,035 3,872
------------- -------------
PROPERTY AND EQUIPMENT, net 30,725 7,224
------------- -------------
DEFERRED FINANCING COSTS, net of accumulated amortization
of $249 and $96 on December 31, 2000 and 1999, respectively 558 251
------------- -------------
OTHER ASSETS 574 167
------------- -------------
Total assets $ 143,892 $ 11,514
============= =============
LIABILITIES AND STOCKHOLDERS' EQUITY
CURRENT LIABILITIES:
Current portion of long-term debt, including amounts due to related parties
of $52 and $0 at December 31, 2000 and
1999, respectively $ 795 $ 1,020
Current portion of capital lease obligations 5,549 1,200
Accounts payable 5,251 820
Accrued expenses 2,111 488
Current portion of deferred revenue 206 39
------------- -------------
Total current liabilities 13,912 3,567
------------- -------------
LONG-TERM LIABILITIES:
Long-term debt, including amounts due to related parties of $4,752 and $950
at December 31, 2000 and 1999, respectively,
less current portion 5,305 2,287
Capital lease obligations, less current portion 15,408 3,842
Deferred revenue, less current portion 2,133 422
Royalty obligations 300 300
Convertible promissory notes - 3,500
Accrued dividends 1,159 1,056
------------- -------------
Total long-term liabilities 24,305 11,407
------------- -------------
THE ACCOMPANYING NOTES ARE AN INTEGRAL PART OF THESE FINANCIAL STATEMENTS.
29
GENAISSANCE PHARMACEUTICALS, INC.
Balance Sheets (Continued)
(Amounts in thousands, except per share data)
DECEMBER 31,
2000 1999
LIABILITIES AND STOCKHOLDERS' EQUITY (CONTINUED)
COMMITMENTS AND CONTINGENCIES (Note 12)
REDEEMABLE CONVERTIBLE PREFERRED STOCK,
1,000 and 10,000 authorized shares at December 31, 2000
and 1999, respectively
Series A and KBL $.001 par value, 0 and 2,438 shares issued
and outstanding at December 31, 2000 and 1999 -- 11,247
------------- -------------
Series B, KBH, and C (Note 8) -- --
------------- -------------
PUTTABLE WARRANT -- 125
------------- -------------
STOCKHOLDERS' EQUITY:
Common stock, 58,000 and 10,000 authorized shares at December 31, 2000 and
1999, respectively; $.001 par value; 22,687, and 2,810
shares issued and outstanding at December 31, 2000 and 1999 23 3
Additional paid-in capital 218,525 4,819
Accumulated deficit (112,927) (19,654)
Net unrealized investment gains 54 --
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Total stockholders' equity 105,675 (14,832)
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Total liabilities and stockholders' equity $ 143,892 $ 11,514
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THE ACCOMPANYING NOTES ARE AN INTEGRAL PART OF THESE FINANCIAL STATEMENTS.
30
GENAISSANCE PHARMACEUTICALS, INC.
Statements of Operations
(Amounts in thousands, except per share data)
YEAR ENDED DECEMBER 31,
2000 1999 1998
REVENUES:
License revenue $ 678 $ 123 $ 87
Grant revenue 75 557 1,256
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