Peptide purification strategies

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Särö Conference 2009 Peptide purification strategies Ulf Altenhöner Lonza Exclusive Synthesis R&D

Outline Introduction Integrated process development Model-based process development Inspiration Conclusions slide 2

The leading supplier to the life-science industries Production facilities worldwide Europe (CH, UK, CZ, BE, SP, F, D) USA Asia Business activities LES - APIs & Intermediates, Synthetic and recombinant Peptides LBP - Biopharmaceuticals LSI - Agrochemicals & organic intermediates LBS - Therapeutic Cells slide 3

Lonza s History in Peptides and Oligos 1980 First peptide production Braine-l Alleud, Belgium 2002 First oligonucleotide production in Visp 1999 Synthetic peptide production in Visp (solid phase synthesis) 2005 $20 million Tides investment in Visp (capacity enlargement, mid-scale plant, lyophylization, infrastructure) 1997 First peptide production in Visp, Switzerland (recombinant technology) 2006 Lonza acquires UCB Bioproducts 2002 Dedicated Tides team in Visp formed (R&D, QC, QA) Peptides slide 4

Custom Manufacturing: Focused on Late Stage Development Discovery Development Manufacture Distribution basic research disease discovery drug discovery drug development clinical trials production packaging marketing sales distribution Products Early intermediates Advanced intermediates Bulk actives/ drug substance lab supply clinical supply launch supply in- market supply A Broad Range of Production Scales Assists lifecycle management Increases flexibility Enables seamless scale-up slide 5

Requirements for an Industrial API manufacturing process Quality by Design Concept Structured Process Development ensures consistent delivery of quality, safety and efficacy objectives Ensures process robustness Process scalability Continuous improvement Competitive process, determined by: Yield Productivity Number of unit operations Cost of goods slide 6

Outline Introduction Integrated process development Model-based process development Inspiration Conclusions slide 7

Simmrock The sum of the optimal process steps is not equal to the optimal process! From Prof. Dr. rer. nat. K. H. Simmrock, Dortmund around 1990 slide 8

Customer requirements Typical customer request: product is a peptide/protein (10 to 50 amino acids) delivery 1 kg 95 to 99% pure within 6 months after request for proposal eventually single impurities specified lyophilized as salt (e.g. acetate) established laboratory process slide 9

Process Sketch Structure formation Purification Concentration / Buffer exchange Isolation Product acc. Specifications slide 10

Integrated process development Multi step approach: step 1: run a best process structure formation step 2: run a best process purification step 3: identify critical impurities in purification use structure elucidating techniques (LC-MS, NMR etc.) step 4: give feedback for structure formation step 5: run improved structure formation step X: stop when: a: no improvement is achieved anymore b: proces performance targets are achieved slide 11

Example: Structure formation by Solid-Phase Peptide Synthesis coupling of the first amino-acid Amino-acid coupling Amino-acid coupling OH Fmoc deprotection OH Fmoc deprotection OH X X X X X Repeat n times cleavage + deprotection Schema by Prof. F. Albericio, Institut de Recerca Biomèdica, Barcelona, IRB-PCB H OH slide 12

Impurities! During the peptide assembly in SPPS the following impurities will be formed: Impurities in starting materials Impurities formed during peptide elongation Isomers Double hits Deletion products Side products from reactions with coupling reagents, deprotection reagents or solvents Side products from other reactions on side chain functionalities slide 13

Example 1: Impurities! double hit AA, deletions, diastereomers H OH H OH H OH H OH H H OH H OH H OH Main product OH slide 14

Evaluation of impurity influences Score 1: Yield loss in structure formation Score 2: Yield loss in purification Score 3: Productivity limiting in purification slide 15

Example 2: Integrated Process Development Purification by RP-HPLC Crude peptide Pure peptide 0.0280 43.154 0.024 BR-015-44.226 0.0224 42.784 0.018 0.0168 AU 43.662 AU 0.012 43.863 0.0112 0.0056 40.263 40.798 41.085 41.317 41.826 42.598 44.065 44.452 44.906 45.210 45.591 0.006 0.000 42.069 42.286 42.921 43.461 44.857 45.661 40.20 40.80 41.40 42.00 42.60 43.20 43.80 44.40 45.00 45.60 Minutes 40.20 40.80 41.40 42.00 42.60 43.20 43.80 44.40 45.00 45.60 Minutes Peptide Area%: 58.9% RRT 0.99: 8.9% Peptide Area%: 94.9% RRT 0.99: 3.5% RRT 0.99 was identified via MS/MS: AA double hit slide 16

Example 2: Integrated Process Development Results Reaction # Time Coupling reagent Temperature Conversion (h) C % 1 72 TCTU 20 92.2% 2 7 DIC / 6-Cl-HOBt 40 99.6% Crude peptide Pure peptide 0.024 BR-015-44.226 0.030 BR-015-44.375 0.024 0.018 0.018 AU 0.012 43.863 AU 0.012 0.006 0.000 42.069 42.286 42.921 43.461 44.857 45.661 0.006 41.690 42.176 42.780 43.154 43.599 44.045 45.131 45.382 40.20 40.80 41.40 42.00 42.60 43.20 43.80 44.40 45.00 45.60 Minutes 40.20 40.80 41.40 42.00 42.60 43.20 43.80 44.40 45.00 45.60 Minutes Peptide Area%: 75.3% RRT 0.99: 0.9% Peptide Area%: 98.8% RRT 0.99: 0.3% slide 17

Outline Introduction Integrated process development Model-based process development Inspiration Conclusions slide 18

Model-based Process Optimization Example The Peptide: Lonza Code XX-003-4 kda polypeptide (39 AA) Produced by solid-phase synthesis The Process: 2-step chromatographic process 1 st step: H 2 O-AcN, TEAP buffer 2 nd step: H 2 O-AcN, AcOH buffer Overall Yield: 51.3% (no recycled fractions) Overall Productivity: 0.012 g/l/min Specifications: Overall purity 97% Max. single impurity <1% slide 19

Model-based Process Optimization The Strategy Model calibration for pure component Impurity characterization Selectivity 1 Concentration modifier Pareto optimization of gradient & load productivity [mg/ml/min] 0 0.2 0.4 0.6 0.8 1 yield [-] at 99% purity Optimal batch process peptide concentration [g/l] modifier concentration [g/l] Time [min] slide 20

Pure Component Parameter Estimation First Chromatographic Step (TEAP) Henry coefficient slide 21

Pure Component Parameter Estimation First Chromatographic Step (TEAP) Full Isotherm Estimation Linear Conditions Overloaded Conditions slide 22

Pure Component Parameter Estimation First Chromatographic Step (TEAP) Anti-Langmurian behavior with gradient elutions Moreau Isotherm Account for adsorbate-adsorbate interactions Loading Gradient: 20-70%B in 30min slide 23

Bi-Moreau Isotherm The Equations Langmuir behavior Equilibrium Adsorption Surface Anti-Langmuir behavior slide 24

Model-based Process Optimization The Strategy Model calibration for pure component Impurity characterization Selectivity 1 Concentration modifier Pareto optimization of gradient & load productivity [mg/ml/min] 0 0.2 0.4 0.6 0.8 1 yield [-] at 99% purity Optimal batch process peptide concentration [g/l] modifier concentration [g/l] Time [min] slide 25

Impurity Parameter Estimation First Chromatographic Step (TEAP) Characterization of key impurities slide 26

Model-based Process Optimization The Strategy Model calibration for pure component Impurity characterization Selectivity 1 Concentration modifier Pareto optimization of gradient & load productivity [mg/ml/min] 0 0.2 0.4 0.6 0.8 1 yield [-] at 99% purity Optimal batch process peptide concentration [g/l] modifier concentration [g/l] Time [min] slide 27

Model-based Process Optimization Pareto Curve (95% purity) Productivity vs Yield slide 28

Model-based Process Optimization Pareto Curve (95% purity) Loading vs Yield Loading [mg/ml] slide 29

Model-based Process Optimization The Strategy Model calibration for pure component Impurity characterization Selectivity 1 Concentration modifier Pareto optimization of gradient & load productivity [mg/ml/min] 0 0.2 0.4 0.6 0.8 1 yield [-] at 99% purity Optimal batch process peptide concentration [g/l] modifier concentration [g/l] Time [min] slide 30

Optimal Batch Process Experimental Validation chosen point current method experimental result slide 31

Optimal Batch Process Experimental Validation Simulation of recommended gradient XX003 slide 32

Optimal Batch Process Experimental Validation Experimental verification: UV + fraction analysis concentration [g/l] 12 10 8 6 4 L L1 L2 L3 Prod H1 H2 H UV signal calib Sim Modifier 450 400 350 300 250 200 2 150 100 0 0 5 10 15 20 25 30 35 40 50-2 time [min] 0 slide 33

Process Summary Chromatography 1 + 2 Experimental validation Old LONZA New ETH Process Process 1st purification column load [mg/ml] 5.6 3.44 purity [%] 95 95 yield [%] 57 80 productivity [mg/ml/min] 0.023 0.054 process time [min] 140 57 Recycle 1st purification percentage recycled [%] 17 18 yield recycling [%] 36 70 load recyle [mg/ml] 8 1.5 main runs per recycle 8.40 2 productivity [mg/ml/min] 0.021 0.021 OVERALL 1st purification purity [%] 95 95 yield [%] 63.12 92.6 productivity [mg/ml/min] 0.023 0.044 Old LONZA New ETH Process Process 2nd purification column load [mg/ml] 8 6.17 purity [%] 97 97 yield [%] 74 89.4 productivity [mg/ml/min] 0.06 0.128 process time [min] 100 43 Recycle 2nd purification percentage recycled [%] 20 yield recycling [%] 36 load recyle [mg/ml] 8 main runs per recycle 5 productivity [mg/ml/min] 0.0288 OVERALL 2nd purification purity [%] 97 97 yield [%] 81.2 89.4 productivity [mg/ml/min] 0.05474 0.128 slide 34

Inspiration 0.2 % TFA 0.05 % TFA slide 35

Summary Integrated Process Development: easy to use no tools needed all about communication Model based Process Development: Current process has been largely improved Higher process yield Higher productivity Quality by design can be applied Flexible optimization of production conditions Simpler validation and qualification procedures slide 36

Acknowlegments Ariette Imboden (Lonza) Christine Werlen (Lonza) Dr. Holger Hermann (Lonza) Dr. Patrick Moebius (Lonza) Dr. Francesca Quattrini (Lonza) Dr. Alessandro Butte (Lonza) Prof. Massimo Morbidelli (ETH Zurich) Dr. Guido Ströhlein (ChromaCon AG) Dr. Lars Aumann (ChromaCon AG) Prof. F. Albericio, Institut de Recerca Biomèdica, Barcelona, IRB-PCB Dr. Olav Lyngberg (Bristol-Myers Squibb Company) Dr. Douglas Riexinger (Bristol-Myers Squibb Company) slide 37

Thank you for your attention! slide 38