Exhibit 99.2

©2014 DaVita HealthCare Partners Inc.® All rights reserved. Proprietary. May not be copied, reprinted or distributed without the permission of DaVita HealthCare Partners Inc. Hyperphosphatemia is a nearly ubiquitous consequence of end-stage renal disease (ESRD) and is associated with increased risks of mortality and hospitalization.1-3 Phosphate homeostasis in patients receiving dialysis generally requires dietary phosphate restriction and, frequently, the use of phosphate binders to prevent systemic absorption.4 The iron-based phosphate binder ferric citrate coordination complex (FCCC; Keryx Biopharmaceuticals, Inc.) has recently completed phase 3 clinical trials in the United States and Japan. – In addition to being safe and efficacious as a phosphate binder, clinical trials have shown that FCCC results in a stable and sustained increase in serum ferritin concentrations and transferrin saturation, without evidence of iron overload. – FCCC use also resulted in reduced utilization of ESA and intravenous (IV) iron, with higher hemoglobin (Hb) concentrations and lower hospitalization rates.5-7 Changes to Centers for Medicare and Medicaid Services reimbursement for hemodialysis in recent years have affected dialysis facilities’ financial status, with the costs of providing care exceeding payments received for patients with Medicare as primary payer. Economic Impact of Ferric Citrate Versus Standard of Care For Hemodialysis Patients Steven M Brunelli, MD, MSCE;1 Scott Sibbel, PhD, MPH;1 Amit Sharma, MD;2 Andrew Hsieh, PharmD2 1DaVita Clinical Research, Minneapolis, MN, USA; 2Keryx Biopharmaceuticals Inc., New York, NY, USA Introduction Conclusions References Objective The objective of the current study was to evaluate the budgetary impact of FCCC versus standard of care as first-line phosphate binder from the perspective of a dialysis provider within the context of the current reimbursement paradigm and accounting for the effects of FCCC on ESA and IV iron utilization, Hb concentrations, and the potential for missed hemodialysis sessions resulting from hospitalizations. This net budgetary impact model demonstrates that if FCCC were adopted in wide clinical practice as a first-line phosphate binder rather than the current standard of care, cost savings to the dialysis provider would be approximately $1.2M per year per 1,000 patients receiving phosphate binder. – Estimated cost savings arise principally from reductions in injected drug utilization and missed dialysis sessions. – The model assessed net budgetary impact of FCCC under current reimbursement, where oral medications are reimbursed separately from dialysis. The potential range of cost savings will depend in part on how physicians adjust ESA dose in response to the +0.3 g/dL differential in Hb concentration seen in FCCC-treated patients compared to control patients; sensitivity analyses suggest a range of $1.0M to $1.5M per year per 1,000 patients receiving phosphate binder. We extend our sincere appreciation to the teammates in more than 2,000 DaVita clinics who work every day to take care of patients and also to ensure the extensive data collection on which our work is based. We thank DaVita Clinical Research® (DCR®), and specifically acknowledge Abigail Hunt, PhD, of DCR for editorial contributions in preparing this poster. DCR is committed to advancing the knowledge and practice of kidney care. This study was funded by Keryx Biopharmaceuticals, Inc. *Correspondence: Steven.Brunelli@davita.com Poster available at www.davitaclinicalresearch.com/publication-directory/ National Kidney Foundation Spring Clinical Meetings, 22-26 April 2014, Las Vegas, Nevada 1. Block GA, Hulbert-Shearon TE, Levin NW, Port FK. Association of serum phosphorus and calcium x phosphate product with mortality risk in chronic hemodialysis patients: a national study. Am J Kidney Dis. 1998;31(4):607-617. 2. Block GA, Klassen PS, Lazarus JM, Ofsthun N, Lowrie EG, Chertow GM. Mineral metabolism, mortality, and morbidity in maintenance hemodialysis. J Am Soc Nephrol. 2004;15(8):2208-2218. 3. Kalantar-Zadeh K, Kuwae N, Regidor DL, Kovesdy CP, Kilpatrick RD, Shinaberger CS, et al. Survival predictability of time-varying indicators of bone disease in maintenance hemodialysis patients. Kidney Int. 2006;70(4):771-780. 4. K/DOQI clinical practice guidelines for bone metabolism and disease in chronic kidney disease. Am J Kidney Dis. 2003;42(4 Suppl 3):S1-S201. 5. Yokoyama K, Hirakata H, Akiba T, Sawada K, Kumagai Y. Effect of oral JTT-751 (ferric citrate) on hyperphosphatemia in hemodialysis patients: results of a randomized, double-blind, placebo-controlled trial. Am J Nephrol. 2012;36(5):478-487. doi:10.1159/000344008. 6. Sika M, Umanath K, Goral S, Arfeen S, Bowline I, Chernin G, et al. Ferric citrate as a phosphate binder has a safety profile similar to sevelamer carbonate and calcium acetate. J Am Soc Nephrol. 2013;24:751A. 7. Lewis J, Dwyer J, Koury M, Sika M, Schulman G, Smith M, et al. Ferric citrate binds phosphorus, delivers iron, and reduces IV iron and erythropoietic stimulating agent use in end-stage renal disease. J Am Soc Nephrol. 2013;24:751A. 8. Umanath K, Blumenthal S, Sika M, Greco B, Jalal D, Reisin E, et al. Ferric citrate as a phosphate binder reduces IV iron and erythropoietin stimulating agent (ESA) use. J Am Soc Nephrol. 2013;24:221A. We constructed a Markov microsimulation model using TreeAge Pro 2013 (TreeAge Software Inc., Williamston, MA). The model considered 21 health states: 20 based on permuted categories of serum phosphate and phosphate binder dose strength; the 21st state was death, which was an absorbing state. We modeled serum phosphate and phosphate binder dose strength as continuous tracer variables and modeled the mutually referential, longitudinal effects between the two (Figure 1). For each interval, probability of death, hemodialysis treatment attendance, ESA utilization, and IV iron utilization were probabilistically assigned conditional upon health state. Methods Acknowledgments QR CODE Results Results Base-Case Model Sensitivity Analyses Limitations of the Model Data do not pertain to net budgetary impact in the context of a more comprehensive bundle, under which dialysis providers assume financial responsibility for the costs of oral drugs. Cost savings pertain to patients treated with FCCC and not those who do not receive phosphate binders. Payer mix among phosphate binder initators is skewed toward higher prevalence of commercial payers because such patients are, on average, younger than the overall dialysis population. Extrapolation of findings to a facility- or provider-level should therefore be undertaken cautiously. Data used to estimate costs were derived based on contracted rates for a single provider; actual costs will vary across provider organizations. Patient 1 Phos1 Binder1 Phos2 Binder2 From starting distribution Determines: Treatments received1 ESA use1 IV iron use1 Death1 Determines: Treatments received2 ESA use2 IV iron use2 Death2 Figure 1. Schematic Depiction of the Microsimulation Model Patient is probabilistically assigned a starting serum phosphate level (Phos1) based on the empiric distribution of phosphate levels that immediately preceded phosphate binder initation. Phosphate binder dose strength for cycle 1 (Binder1) is assigned probabilitistically conditional on Phos1. Phos1 and Binder1 determine the patient’s health state for cycle 1, which probabilistically determines the number of dialysis treatments, total dose of ESA and IV iron, and probability of death during cycle 1. For patients who survive cycle 1, change in phosphate between cycle 1 and cycle 2 is probabilitistically sampled based on Phos1 and Binder1. Change in phosphate binder strength at the start of cycle 2 is probabilistically sampled conditional on Phos2 and Binder1. Phos2 and Binder2 then define the health state for cycle 2. This process iterates forward. We ran the model over a 1-year time horizon and considered a 1-month cycle length. We used combined first and second order Monte Carlo simulation to fit models. Each model considered 1000 second-order trials. Model input data were derived from a retrospective analysis of phosphate binder users from a large dialysis organization (LDO). Patients received in-center hemodialysis at the LDO between January 2011 and June 2013, were enrolled in the LDO’s pharmacy management program, and were incident users of phosphate binders. Patients were considered for a maximum of 24 months or until censoring (death, transfer, modality change, transplant, end of study period). Effects of FCCC were taken from results of the 52-week open-label safety portion of a recently completed phase III clinical trial (Keryx Biopharmaceuticals Inc., data on file). Costs and revenues were based on actual rates paid/received by the LDO (proprietary) and were considered in fixed 2013 USD. Costs and revenues considered were revenue for attended treatments, fixed costs of providing dialysis, cost of ESA, remuneration for ESA , cost of IV iron (drug and associated peripherals), and payment for IV iron. Phosphate binder costs were not included in the model as these are not borne by dialysis facilities under current reimbursement policies. Methods Under base-case assumptions and considered over 1 year, treatment with FCCC versus standard of care was found to have a net budgetary impact of +1,188,337 USD/year for 1,000 patients receiving phosphate binder (Table 2). In a phase 3 clinical trial, mean Hb was +0.3 g/dL higher in FCCC-treated compared to control-treated patients. If the magnitude of the Hb differential is sufficient to prompt ESA down-titration in FCCC-treated patients, then further reductions in ESA utilization could result. – We assessed scenarios in which the increase in Hb translated into 0%, 10% (base case), 20%, or 30% additional reduction in ESA. Net budgetary impact ranged from +1,042,204 to +1,474,917 USD/year/1,000 patients receiving phosphate binder (Table 3). Clinical trial data indicate that FCCC use results in a 24% lower hospitalization rate. In base-case models, we assumed that the number of missed treatments corresponded 1:1 with hospitalizations. – Varying the ratio of missed sessions to hospitalizations to 1.25:1 or 1.5:1 resulted in a net budgetary impact of FCCC of +1,268,391 and +1,290,981 USD/year per 1,000 patients treated with phosphate binder, respectively (Table 3). Table 1. Base Case Model Inputs Value Model inputs derived from retrospective analysis of incident phosphate binder users at LDO Mean (SD) starting serum phosphate, mg/dL 5.4 (1.6) Distribution of primary insurance Medicare 85% Private 15% PB mix (standard of care) Calcium acetate 45% Sevelamer 47% Lanthanum carbonate 7% Starting PB strength based on starting serum phosphatea Serum phosphate < 3.5 mg/dL, starting PB strength 1 19.9% 1.5 27.7% 2 52.4% Serum phosphate = 3.5-5.5 mg/dL, starting PB strength 1 19.6% 1.5 23.1% 2 57.4% Serum phosphate = 5.6-6.5 mg/dL, starting PB strength 1 17.8% 1.5 21.2% 2 61.0% Serum phosphate > 6.5 mg/dL, starting PB strength 1 13.4% 1.5 17.2% 2 69.4% Model inputs derived from FCCC clinical trial Effects of FCCC ESA dose 36% reduction Effect of higher Hb on ESA dose 10% additional reduction IV iron dose 55% reduction IV iron administrations 59% reduction Objective a. Phosphate binder dose strength categories: Dose Strength +1 = calcium acetate 1-2001 mg; sevelamer 1-2400 mg; lanthanum carbonate 1-3000 mg Dose Strength +1.5 = calcium acetate 2002-4002 mg; sevelamer 2401-4800 mg; lanthanum carbonate 3001-6000 mg Dose Strength +2 = calcium acetate > 4002 mg; sevelamer > 4800 mg; lanthanum carbonate > 6000 mg Abbreviations: ESA, erythropoiesis-stimulating agent; FCCC, ferric citrate coordination complex; Hb, hemoglobin; IV, intravenous; PB, phosphate binder; SD, standard deviation Table 2. Net Budgetary Impact: Base-Case Model Net Budgetary Impact of FCCC vs SOC (USD/year) Mean (SEM) Median (p25, p75) P-value Number of patients treated with phosphate binder Per 80 patients +95,071 +94,948 < 0.001 (7,385) (+89,842; +100,254) Per 1,000 patients +1,188,337 +1,188,885 < 0.001 (26,490) (+1,170,228; +1,206,570) Per 10,000 patients +11,868,830 +11,866,750 < 0.001 (83,895) (+11,815,720; +11,924,160) Per 100,000 patients +118,695,600 +118,698,400 < 0.001 (262,404) (+118,516,400; +118,873,200) Abbreviations:FCCC, ferric citrate coordination complex; SEM, standard error of mean; SOC, standard of care; USD, United States dollars Table 3. Net Budgetary Impact: One-Way Sensitivity Analyses Net Budgetary Impact of FCCC vs SOC (USD/year/1000 patients treated) Mean (SEM) P-value Implication of Hb differential on ESA utilization, +0.3 g/dL higher Hb results in: 0% further reduction in ESA +1,042,204 (23,315) < 0.001 10% further reduction in ESA (base case) +1,188,337 (26,490) < 0.001 20% further reduction in ESA +1,331,169 (29,806) < 0.001 30% further reduction in ESA +1,474,917 (34,033) < 0.001 Ratio of missed treatments to hospitalizations: 1:1 (24% reduction in missed treatments; base case) +1,188,337 (26,490) < 0.001 1:1.25 (30% reduction in missed treatments) +1,268,391 (27,204) < 0.001 1:1.5 (36% reduction in missed treatments) +1,290,981 (28,400) < 0.001 Abbreviations: ESA, erythropoiesis-stimulating agent; FCCC, ferric citrate coordination complex; Hb, hemoglobin; SEM, standard error of mean; SOC, standard of care; USD, United States dollars Davin Clinical Research.