UCL Decisional Tools Research Operational & Economic Evaluation of Integrated Continuous Biomanufacturing Strategies for Clinical & Commercial mAb Production Suzanne Farid PhD CEng FIChemE Reader (Associate Professor) Co-Director EPSRC Centre for Innovative Manufacturing UCL Biochemical Engineering s.farid@ucl.ac.uk ECI Integrated Continuous Biomanufacturing, Barcelona, Spain, 20-24 October 2013

Acknowledgements Engineering Doctorate Project: Evaluating The Potential of Continuous Processes for Monoclonal Antibodies: Economic, Environmental and Operational Feasibility UCL-Pfizer Collaboration (2008-2013) UCL academic collaborators included: Daniel Bracewell (ex-)Pfizer collaborators included: Glen Bolton, Jon Coffman Funding: UK EPSRC, Pfizer James Pollock UCL Suzanne Farid UCL Sa Ho Pfizer

Farid, 2012, In Biopharmaceutical Production Technology, pp717-74 Bioprocess Decisional Tools – Domain Biotech Drug Development Cycle Farid, 2012, In Biopharmaceutical Production Technology, pp717-74 3

Scope of UCL Decisional Tools Typical questions addressed: Process synthesis & facility design Which manufacturing strategy is the most cost-effective? How do the rankings of manufacturing strategies change with scale? Or from clinical to commercial production? Key economic drivers? Economies of scale? Probability of failing to meet cost/demand targets? Robustness? Portfolio management & capacity planning Portfolio selection - Which candidate therapies to select? Capacity sourcing - In-house v CMO production? Impact of company size and phase transition probabilities on choices? Is it media, resins, OHs? 4

Scope of UCL Decisional Tools Systems approach to valuing biotech / cell therapy investment opportunities Process synthesis and facility design Capacity planning Portfolio management Challenges: Capturing process robustness under uncertainty & reconciling conflicting outputs Fed-batch versus perfusion systems (Lim et al, 2005 & 2006; Pollock et al, 2013a) Continuous chromatography (Pollock et al, 2013b) Integrated continuous processing (Pollock et al, submitted) Stainless steel versus single-use facilities (Farid et al, 2001, 2005a &b) Facility limits at high titres (Stonier et al, 2009, 2012) Single-use components for allogeneic cell therapies (Simaria et al, 2013) Adopting efficient methods to search large decision spaces Portfolio management & capacity planning (Rajapakse et al, 2006; George & Farid, 2008a,b) Multi-site long term production planning (Lakhdar et al, 2007; Siganporia et al, 2012) Chromatography sequence and sizing optimisation in multiproduct facilities (Simaria et al, 2012; Allmendinger et al, 2012) Integrating stochastic simulation with advanced multivariate analysis Prediction of suboptimal facility fit upon tech transfer (Stonier et al, 2013; Yang et al, 2013) Creating suitable data visualization methods For each of above examples Farid, 2012, In Biopharmaceutical Production Technology, pp717-74

Scope of UCL Decisional Tools Systems approach to valuing biotech / cell therapy investment opportunities Process synthesis and facility design Capacity planning Portfolio management Challenges: Capturing process robustness under uncertainty & reconciling conflicting outputs Fed-batch versus perfusion systems (Pollock et al, 2013a) Continuous chromatography (Pollock et al, 2013b) Integrated continuous processing (Pollock et al, submitted) Stainless steel versus single-use facilities (Farid et al, 2001, 2005a &b) Facility limits at high titres (Stonier et al, 2009, 2012) Single-use components for allogeneic cell therapies (Simaria et al, submitted) Adopting efficient methods to search large decision spaces Portfolio management & capacity planning (Rajapakse et al, 2006; George & Farid, 2008a,b) Multi-site long term production planning (Lakhdar et al, 2007; Siganporia et al, 2012) Chromatography sequence and sizing optimisation in multiproduct facilities (Simaria et al, 2012) Integrating stochastic simulation with advanced multivariate analysis Prediction of suboptimal facility fit upon tech transfer (Stonier et al, 2013; Yang et al, 2013) Creating suitable data visualization methods For each of above examples Farid, 2012, In Biopharmaceutical Production Technology, pp717-74

Scope of UCL Decisional Tools Systems approach to valuing biotech / cell therapy investment opportunities Process synthesis and facility design Capacity planning Portfolio management Challenges: Capturing process robustness under uncertainty & reconciling conflicting outputs Fed-batch versus perfusion systems (Pollock et al, 2013a) Scenario: New build for commercial mAb prodn Impact of scale on cost Impact of titre variability and failures rates on robustness Continuous chromatography (Pollock et al, 2013b) Scenario: Retrofit for clinical / commercial mAb prodn Impact of scale and development phase on cost Retrofit costs across development phases Integrated continuous processing (Pollock et al, submitted) Scenario: New build for clinical / commercial mAb prodn Impact of hybrid batch/continuous USP and DSP combinations Impact of development phase, company size and portfolio size

Pollock, Ho & Farid, 2013, Biotech Bioeng, 110(1): 206–219 Fed-batch versus perfusion culture (New build) Fed-batch versus perfusion systems (Pollock et al, 2013a) Scenario: New build for commercial mAb prodn Impact of scale on cost Impact of titre variability and failures rates on robustness Pollock, Ho & Farid, 2013, Biotech Bioeng, 110(1): 206–219 8 8

Pollock, Ho & Farid, 2013, Biotech Bioeng, 110(1): 206–219 Fed-batch versus perfusion culture (New build) Commercial products using perfusion cell culture technologies Pollock, Ho & Farid, 2013, Biotech Bioeng, 110(1): 206–219 9 9

Pollock, Ho & Farid, 2013, Biotech Bioeng, 110(1): 206–219 Fed-batch versus perfusion culture (New build) Scenario trade-offs: FB v SPIN v ATF Spin-filter Perfusion ATF Perfusion Steady state cell densities Failure rates SPIN FILTER LIQUID LEVEL PRO: Investment DSP consumable cost CON: Equipment failure rate USP consumable cost Scale limitations Validation burden Compare the cost-effectiveness and robustness of fed-batch and perfusion cell culture strategies across a range of titres and production scales for new build Pollock, Ho & Farid, 2013, Biotech Bioeng, 110(1): 206–219 10 10

Pollock, Ho & Farid, 2013, Biotech Bioeng, 110(1): 206–219 Fed-batch versus perfusion culture (New build) Key assumptions Suites FB SPIN ATF Cell Culture Suite DSP Suite Viral Secure Suite Seed #1 Seed #2 CC Cent DF UF ProA VI CEX UFDF VRF AEX Pool Variable FB SPIN ATF Reactor type SS/SUB SS SUB Cell culture time (days) 12 60 Max VCD (106 cells/ml) 10 15 50 Max bioreactor vol. (L) 20,000 2000 1500 Max perf. rate (vv/day) – 1 1.5 Process yield 65% 68% 69% Annual # batches 22 5 Product conc. (g/L) 2 – 10 20% FB 45% FB Productivity (mg/L/day) 170-850 2 x FB 6.5 x FB Pollock, Ho & Farid, 2013, Biotech Bioeng, 110(1): 206–219 11 11

Pollock, Ho & Farid, 2013, Biotech Bioeng, 110(1): 206–219 Fed-batch versus perfusion culture (New build) Results: Impact of scale on COG = Indirect = Material = Labour Comparison of the cost of goods per gram for an equivalent fed-batch titre of 5 g/L Critical cell density difference for ATF to compete with FB - x3 fold. Pollock, Ho & Farid, 2013, Biotech Bioeng, 110(1): 206–219 12 12

Pollock, Ho & Farid, 2013, Biotech Bioeng, 110(1): 206–219 Fed-batch versus perfusion culture (New build) Uncertainties and failure rates Process event p(Failure) Consequence Fed-batch culture contamination 1 % Batch loss Spin-filter culture contamination 6 % Batch loss & discard two pooled perfusate volumes Spin-filter filter failure 4 % Batch loss & no pooled volumes are discarded ATF culture contamination ATF filter failure 2 % Replace filter & discard next 24 hours of perfusate In process filtration failure – general 5 % 4 hour delay & 2% yield loss In process filtration failure– post viral inactivation 20 % Pollock, Ho & Farid, 2013, Biotech Bioeng, 110(1): 206–219 13 13

Pollock, Ho & Farid, 2013, Biotech Bioeng, 110(1): 206–219 Fed-batch versus perfusion culture (New build) Results: Impact of variability on robustness Annual throughput and COG distributions under uncertainty 500kg demand, 5g/L titre Pollock, Ho & Farid, 2013, Biotech Bioeng, 110(1): 206–219 14 14

Pollock, Ho & Farid, 2013, Biotech Bioeng, 110(1): 206–219 Fed-batch versus perfusion culture (New build) Results: Impact of variability on robustness Annual throughput and COG distributions under uncertainty 500kg demand, 5g/L titre Pollock, Ho & Farid, 2013, Biotech Bioeng, 110(1): 206–219 15 15

Fed-batch versus perfusion culture (New build) Results: Reconciling operational and economic benefits FB ATF SPIN FB = ATF SPIN ATF FB SPIN Operational benefits dominate Economic benefits dominate ─ fed-batch, -- spin-filter, ··· ATF Pollock, Ho & Farid, 2013, Biotech Bioeng, 110(1): 206–219 16 16

Continuous chrom: clinical & commercial (Retrofit) Continuous chromatography (Pollock et al, 2013b) Scenario: Retrofit for clinical / commercial mAb prodn Impact of scale and development phase on cost Retrofit costs across development phases Pollock, Bolton, Coffman, Ho, Bracewell, Farid, 2013, J Chrom A, 1284: 17-27 17 17

Technology Evaluation Continuous chrom: clinical & commercial (Retrofit) Technology Evaluation 1 ml scale-down evaluation 3C-PCC system validation Discrete event simulation tool Load FT Load FT Wash Mass balance, scale-up & scheduling equations

Continuous chrom: clinical & commercial (Retrofit) Example Chromatogram ramp-up ramp-down Switch time 3C-PCC CV = 3 x 1 mL Titre = 2 g/L tres = 6.6 mins tSwitch = 200 mins trampup = 330 mins trampdown = 300 mins

Continuous chrom: clinical & commercial (Retrofit) Product Quality (Elution peak) CEX - HPLC Acidic Designated Basic Cycle (100 cycles) 19.3 % 75.0 % 5.7 % Batch (3 cycles) 18.4 % 74.7 % 6.8 % 3C-PCC (6 runs) 18.3 % 75.8 % 5.9 % SEC - HPLC HMW Designated LMW Cycle (100 cycles) 0.7 % 97.6 % 1.7 % Batch (3 Cycles) 1.0 % 96.9 % 2.1 % 3C-PCC (6 runs) 0.4 % 98.0 % 1.6 %

Technology Evaluation Continuous chrom: clinical & commercial (Retrofit) Technology Evaluation 1 ml scale-down evaluation 3C-PCC system validation Discrete event simulation tool Load FT Load FT Wash Mass balance, scale-up & scheduling equations

Continuous chrom: clinical & commercial (Retrofit) Early phase DS manufacture challenges Proof-of-concept (Phase I & II) ~ 4kg DS for the average mAb 1,2 1800L (wv) Fed-batch @ 2.5g/L Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 PA (1 cycle) (2 cycle) AEX VRF UFDF Protein A resin costs ~ 60% Direct manufacturing costs ~ $250k per molecule 1. Simaria, Turner & Farid, 2012, Biochem Eng J, 69, 144-154 2. Bernstein, D. F.; Hamrell, M. R. Drug Inf. J. 2000, 34, 909–917. Pollock, Bolton, Coffman, Ho, Bracewell, Farid, 2013, J Chrom A, 1284: 17-27

Proof-of-concept (Phase I & II) ~ 4kg DS for the average mAb (2.5g/L) Continuous chrom: clinical & commercial (Retrofit) Results: Economic Impact – Protein A Proof-of-concept (Phase I & II) ~ 4kg DS for the average mAb (2.5g/L) Standard 3C-PCC Load Load Wash 31.4L 3 x 4.9L = 14.7L 5 cycles 17 cycles $ 250K resin $ 118K resin 8 hour shift 24 hour shift 53% reduction in resin volume 40% reduction in buffer volume x2.3 increase in man-hours

Continuous chrom: clinical & commercial (Retrofit) Results: Impact of scale on direct costs PA costs Other Costs 1 x 4kg 4 x 10kg 20 x 10kg Pollock, Bolton, Coffman, Ho, Bracewell, Farid, 2013, J Chrom A, 1284: 17-27

Continuous chrom: clinical & commercial (Retrofit) Results: Impact of development phase on retrofitting investment STD: ÄKTA process (15-600L/hr) + 0.4m column x4 Investment ~8 PoC batches PoC (1 x 4kg) 4C-PCC (15-600L/hr) + 4 x 0.2m columns STD: ÄKTA process (45-1800L/hr) + 0.5m column x3.3 Investment ~25 PIII batches or ~ 8 PoC batches PIII & Commercial (4 x 10kg) 4C-PCC (15-600L/hr) + 4 x 0.3m columns

Pollock, Ho & Farid, submitted Integrated continuous processes (New build) Scenarios: Alternative integrated USP and DSP flowsheets Integrated continuous processing (Pollock et al, submitted) Scenario: New build for clinical / commercial mAb prodn Impact of hybrid batch/continuous USP and DSP combinations Impact of development phase, company size and portfolio size DSP scheduling batch process sequence continuous + batch process sequence continuous process sequence Pollock, Ho & Farid, submitted Company Size Pre-clinical PoC Large 20 14 Medium 10 7 Small 5 3

Integrated continuous processes (New build) Results: Impact of development phase and company size on optimal Strategies USP Capture Polishing Base case Fed-batch Batch FB-CB Continuous ATF-CB ATF perfusion FB-CC ATF-CC Batch USP + Continuous Capture Batch Polishing For early phase and SME – ATF-SUB + Cont Capt + CP optimal Ranking switches as move thru devt stages For commercial and large – FB + Cont Capt + BP optimal ATF processes become less promising with larger demands and product numbers. When ATF is linked to Continuous DSP, it requires an individual purification train per reactor. And so when multiple parallel trains are needed more costly to install. Cont chrom appears to offer advantages in all combos given redn in vol expensive PrA resin required and generates a more concentrated elution pool allowing smaller viral filtration, reducing both direct and indirect batch costs." [refers to VF filter as second biggest cost after proA] Polishing switches from continuous to batch as Shorter processing time in conti (10h to 2-3h) means larger VF areas required (check data) When compounded with mutliple sub-batches in conti - leads to VF costs dominating material costs Results in conti polishing > than batch polishing Continuous USP + Continuous Capture Continuous Polishing

Summary Process economics case study insights: Fed-batch versus perfusion culture for new build Economic competitiveness of perfusion depends on cell density increase achievable and failure rate Continuous chromatography retrofit Continuous capture can offer more significant savings in early-stage clinical manufacture than late-stage Integrated continuous processes for new build Integrated continuous processes offer savings for smaller portfolio sizes and early phase processes Hybrid processes (Batch USP, Continuous Chrom) can be more economical for larger / late phase portfolios

UCL Decisional Tools Research Operational & Economic Evaluation of Integrated Continuous Biomanufacturing Strategies for Clinical & Commercial mAb Production Suzanne Farid PhD CEng FIChemE Reader (Associate Professor) Co-Director EPSRC Centre for Innovative Manufacturing UCL Biochemical Engineering s.farid@ucl.ac.uk ECI Integrated Continuous Biomanufacturing, Barcelona, Spain, 20-24 October 2013

Backup

3 Column Periodic Counter Current Chromatography Continuous chrom: clinical & commercial (Retrofit) 3 Column Periodic Counter Current Chromatography Load FT Wash/ Elution Load Load FT Wash/ Elution FT Pollock, Bolton, Coffman, Ho, Bracewell, Farid, 2013, J Chrom A, 1284: 17-27

Continuous chrom: clinical & commercial (Retrofit) 3 Column Periodic Counter Current Chromatography Wash/ Elution Load Load 65 g/L 40 g/L Load FT Wash Load FT Wash/ Elution FT FT Pollock, Bolton, Coffman, Ho, Bracewell, Farid, 2013, J Chrom A, 1284: 17-27

Proof-of-concept (Phase I & II) ~ 4kg DS for the average mAb (2.5g/L) Continuous chrom: clinical & commercial (Retrofit) Results: Environmental Impact Proof-of-concept (Phase I & II) ~ 4kg DS for the average mAb (2.5g/L) STD 3C-PCC -40% e-factor (kg/ kg of protein) STD 3C-PCC Difference Water 5900 5250 -11% Consumable 24.5 13.7 -44% Pollock, Bolton, Coffman, Ho, Bracewell, Farid, 2013, J Chrom A, 1284: 17-27

Integrated continuous processes (New build) Results: Impact of development phase and company size on optimal Strategies USP Capture Base case Fed-batch Batch FB-CB Continuous ATF-CB ATF perfusion FB-CC ATF-CC Batch USP + Continuous Capture Continuous USP + Continuous Capture

Impact of Resin Life Span (MabSelect x100 cycles) Standard cycling study (40mg/ml) Column regeneration (NaOH) 100% breakthrough cycling study x2.2 the load volume vs. standard 19% loss in capacity 12% loss in capacity 30% loss in capacity Insignificant loss < 15 cycles

Commercial Manufacture Feasibility (3C-PCC @ 5g/L) Increasing cycle number Increasing cycle number 16 22 38 16 19 38 Batch 11 – surpasses harvest hold time Batch 6 – surpasses pool vessel volume

Establishing Optimal Switch Time Protein lost All Protein retained Maximum protein challenge Actual FT challenge

Impact of Resin Life Span Loss in DBC vs. cycle number FT protein vs. cycle number Batch ~20% loss After 100 cycles unbound protein in FT 100% BT ~40% loss