Global Landscape in the Development of Biological Products

Transcription

1 Global Landscape in the Development of Biological Products Technical, Preclinical and Clinical Aspects Antonio da Silva, Head Preclinical Development ANVISA, Brasilia, 26 June 2013 a Novartis company

2 Agenda 1 Biologics & biosimilars: An overview 2 Technical development of biosimilars 3 Preclinical development of biosimilars 3 The case for a new paradigm in clinical development 2 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

3 Biologics have revolutionized modern medicine and will continue to do so Borrowed from nature, very complex Highly specific and powerful medicines Treat serious diseases DNA molecule decoded Genetic code cracked Basic biotechnology enabled Commercial biotech firms founded Leading biotech brands emerge Human genome Stem-cell research Gene therapy 1950s 1960s 1970s 1980s 1990s to today Today / future Source: Company websites and annual reports / Note: All trademarks, logos and pictures are the property of the respective owner 3 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

4 As a result, biologics sales are expected to be ~USD 143 bn in 2013 and to grow to ~USD 190 bn by 2018 Global pharmaceutical market, USD billion CAGR (percent) Key market characteristics Therapeutic proteins Majority of current sales from mega blockbusters Monoclonal antibodies (mabs) are largest and fastest growing segment Small molecules ~30% of industry pipeline are biologics Vaccines not included Source: Evaluate Pharma, Feb 2013; Sandoz analysis

5 Access to biologics is a growing issue around the world Almost one-quarter of 46 European countries do not provide access to biologics for arthritis 1 Cancer patients twice as likely as general population to go bankrupt a year after their diagnosis 2 Canadian children with juvenile idiopathic arthritis may not receive "standard" care because pediatric coverage for biologic drugs is limited and inconsistent 3 Only 50% of severe RA patients receive biologics across EU5, US and Japan 4 1 EULAR 2012: Annual Congress of the European League Against Rheumatism 2 Cancer diagnosis as a risk factor for personal bankruptcy, ASCO Access to biologic therapies in Canada for children with juvenile idiopathic arthritis. J.Rheum, September Stakeholder Insight: Rheumatoid Arthritis DMHC2592/ Published 09/ Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

6 Patient access threatened by growing demand and high cost of biologics Estimated daily treatment costs 1 in USD per day 22 The Biologics Boondoggle A breast cancer patient s annual cost for Herceptin is $37,000 1 Small molecule drugs Biopharmaceuticals People with rheumatoid arthritis or Crohn s disease spend $50,000 a year on Humira and those who take Cerezyme to treat Gaucher disease.spend a staggering $200,000 a year the top six biologics already consume 43% of the drug budget for Medicare Part B 1 Source: NY Times, March 2010 Note: All trademarks, logos and pictures are the property of the respective owner 6 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

7 First wave of high-quality biosimilars are gaining acceptance Biosimilars approved in EU Biosimilar % penetration rates in Daily G- CSF class market (Standard Units May 2012) 1 Somatropin 1 6 Filgrastim Source: EMA, Nov Epoetin Australia Netherlands France Italy Germany Spain Average UK Hungary Finland Poland Greece Bulgaria Sweden Czech Republic Romania Source: IMS Health Standard Units May Sandoz biosimilars are marketed in over 50 countries and have over 50 million patient exposure days for the three marketed Sandoz products 2 1 Sandoz analysis / 2 Sandoz Risk Management Plan reports Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

8 Introduction of filgrastim biosimilars in Sep 2008 has significantly increased uptake of G-CSF G-CSF volume, MAT thru Sep Number of syringes 7,298 7,579 5,816 6,160 6,318 6,730 Filgrastim Lenograstim Pegfilgrastim 3,259 3,302 3,329 3,773 4,394 4, Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June This increase in filgrastim use could have potentially increased access for thousands of cancer patients across Europe 1 Compares Oct 11 - Sept 12 vs Oct 10 - Sept 11 from monthly database Note: All values MAT thru September of respective year / Source: IMS Quarterly Database

9 Genuine competition with a level playing field for all biologics will lead to increased innovation Competition and innovation are inextricably linked a virtuous circle Originators should be able to realize fair profit and return on investment Indefinite monopolies lead to stagnation Biosimilars will increase competition and encourage next wave of biologics innovation Innovation Biosimilars Competition Biosimilar development is highly regulated demanding cutting edge technologies and innovative clinical trial designs, opening the door for new approaches that can be applied to new technology platforms 9 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

11 The target-directed biosimilar dev. concept 1. Target definition Reference product variability Target range 2. Target directed Drug product development development Purification process Process development development Bioprocess development Recombinant cell line development Analytics Leveraging biological variability 3. Confirmation of biosimilarity Clinical PK/PD Preclinical Biological characterization Physicochemical characterization 1) Develop highly similar product 2) Confirm biosimilarity Analytical tool box Initial similarity (tpos 1 ) Pilot scale DS Goal posts Confirm similarity Final scale DS Final formulation In vitro/vivo data Final biosimilarity Validated DS Validated DP Analysis reference Analysis reference Cell Line Drug substance Pilot scale Drug substance Final scale Formulation/Drug product DS / DP 3 validation In vitro/vivo models GLP Tox. 1 Technical Proof of Similarity 2 Good Laboratory Practice toxicology studies in animals 3 Drug substance / drug product 11 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013 Phase I (PK/PD) Phase III (confirmatory)

12 mabs are complex... but can be thoroughly characterized using state-of-the-art analytical science 12 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

13 1 State-of-the-art technologies used to create biosimilars that match originator products across multiple quality attributes For monoclonal antibodies typically > 40 different methodologies are applied, analyzing more than 100 different quality attributes Primary structure e.g.: LC-MS intact mass LC-MS subunits Peptide mapping Impurities e.g.: CEX, cief acidic/basic variants LC glycation Peptide mapping deamidation, oxidation, mutation, glycation SEC/FFF/AUC aggregation Biological activity e.g.: Binding assay ADCC assay CDC assay Higher order structure e.g.: NMR CD spectroscopy FT-IR Post translat. modif. e.g.: NP-HPLC-(MS) N-glycans AEX N-glycans MALDI-TOF N-glycans HPAEC-PAD N-glycans MALDI-TOF O-glycans HPAEC-PAD sialic acids RP-HPLC sialic acids Combination of attributes e.g.: MVDA, mathematical algorithms 13 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

14 1 Variability is significant in originator biologics ADCC Potency [% of reference] Post- Shift 2,0 1,6 1,2 0,8 Unfucosylated G0 [% of glycans] Pre-Shift Post- Shift 80 Pre-Shift 0, Expiry Date 0, Expiry Date Monitoring batches of an approved mab revealed a shift in quality Shift in glycosylation (structure) pattern results in different potency in cell-based assays (function) Indication of a change in the manufacturing process Schiestl, M. et al., Nature Biotechnology 29, , 2011) Sandoz observed such shifts in several original products Note: All trademarks, logos and pictures are the property of the respective owner 14 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

15 ADCC (%of Reference) 1 Originator variability is the basis for definition of biosimilarity goal posts Structure (glyco structure) / function (ADCC) relationship bg0-f [rel. %] Variability of reference product Variability observed during cell line development Biologically possible variability Very narrow goalposts for biosimilar 15 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

16 QbD elements in biosimilar development QTPP CQAs Process Risk Assessment Design Space Process Knowledge Control Strategy Establish Quality Target Product Profile the QTPP forms the basis of design for development of the product Determine Critical Quality Attributes linking quality attributes to clinical safety and efficacy Linking process parameters and critical material attributes to CQAs Definition of critical process parameters (CPPs) Optional: Define the design space (multivariate) acceptable process parameter ranges Design and implement control strategy using risk management e.g. by linking CQAs to process capability and detectability Continual Improvement Manage product life cycle, including continuous process verification and continual improvement 16 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

17 Criticality Scoring of Quality Attributes Risk assessment for ranking and prioritizing quality attributes General concept described in A-MAb case study (Tool #1) Criticality Score = f(impact,uncertainty) e.g.: Criticality Score = Impact x Uncertainty (A-MAb) Impact Known or potential consequences on safety and efficacy, considering: Biological activity PK/PD Immunogenicity Safety (Toxicity) Uncertainty Relevance of information e.g. literature prior knowledge in vitro preclinical clinical or combination of information Criticality Score Quantitative measure for an attribute s impact on safety and efficacy. Using best possible surrogates for clinical safety and efficacy Range 2 (very low) 20 (very high) 1 (very low) 7 (very high) Manufacturer s accumulated experience, relevant information, data e.g. literature, prior & platform knowledge, preclinical and clinical batches,in vitro studies, structure-function relationships 17 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

18 uncertainty Target-directed biosimilar development Solving the uncertainty dilemma by using full-factorial function Scoring of Impact & Uncertainty conceptually similar to A-Mab (CS range equal 2-140) 7 Contour Plot of Criticality Score Calculation using a formula Scores reflect the situation where: QAs we know they have high impact rank highest QAs we think they have high impact rank high QAs we know or think they have a modest impact rank in the middle cs < > impact QAs we know or think they have no/low impact rank lowest Development guided by CS scoring and at end of development CS mainly driven by Impact 18 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

19 Quality attributes can be influenced at all stages of cell line and process development... Quality 1 2 Cell line Host cell line. Transfection/amplification pool Genetic set up of production cell line (clone). Process Growth medium composition. Culture conditions (ph, T, aeration,...) USP type (batch, fed batch, perfusion,...) USP regime (duration, fed type, perfusion rate..) Culture history (genetic stability, process stability..) Individual DSP steps Hold times Storage (buffer, container, conditions..) 19 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

20 ...but it is the biology that largely determines similarity Variability of product quality attributes at project start Screening of host cell lines Genetics Screening of transfection pools Screening of clones Physiology Media development Bioprocess development Chemistry DSP dev. Target spec 20 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

21 1 Technical Proof of Similarity 2 Good Laboratory Practice toxicology studies in animals 3 Drug substance / drug product Confirming biosimilarity at the structural and functional level Analytical tool box Cell Line 1) Develop highly similar product 2) Confirm biosimilarity Initial similarity (tpos 1 ) Confirm similarity Final biosimilarity Pilot scale DS Final scale DS Validated DS Goal posts Final formulation Validated DP In vitro/vivo data Analysis reference Drug substance Drug substance Pilot scale Final scale Formulation/Drug product In vitro/vivo models Analysis reference DS / DP 3 validation GLP Tox. Phase I Phase III (PK/PD) (confirmatory) Biosimilarity exercise = comparison of quality attributes (QAs) of the biosimilar product with reference product range Use of a wide range of sensitive and orthogonal analytical methods Head-to-Head analysis with selected reference batches Performed on DS and DP level Comparison of physicochemical and biological characterization results with head-to-head reference batches and target specification Comparison of stability data: intended conditions (=> stability profile) accelerated, stress conditions (=> forced degradation profile) Justification of differences in QAs 21 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

22 Target-directed cell line development Cell lines Process Dev. Pools Pools Clones Clones Clones Selected Clone Hundreds Thousands Hundreds Tens One 96/24/6 well plates Shake flask Lab - scale bioreactor 22 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

23 GP2017 K9/p17 K13/p17 K17/p17 K22/p17 K25/p17 K31/p17 K37/p17 K38/p17 K59/p17 K64/p17 K69/p17 K72/p17 K75/p17 K1/p26 K7/p26 K22/p26 K52/p26 K53/p26 K59/p26 K84/p26 K104/p26 K106/p26 K122/p26 K126/p26 K3/p17 K7/p17 K11/p17 K15/p17 K23/p17 K24/p17 K28/p17 K29/p17 K30/p17 K32/p17 K33/p17 K36/p17 K40/p17 K42/p17 K48/p17 K53/p17 K55/p17 K56/p17 K60/p17 K62/p17 K77/p17 K80/p17 K92/p17 K93/p17 K79/p ( X-X.DS ) / delta.ds Distance to control (originator) GMAP_bG0_F GMAP_bG0 GMAP_bG1 GMAP_bG2 GMAP_bG2S1 GMAP_Man5 GMAP_Man678 GMAP_unk CEX_AP CEX_0K CEX_1K CEX_2K CEX_unk % Viability, Titer Pool P17 P29 P28 P30 P56 P56 P57 P26 P6 P34 P33 P43 P55 P17 P20 P28 P43 P27 P29 P61 GMAP_bG0_F GMAP_bG0 Cell_line SSF3 K1-PD K1-PD K1-PD HPT2 HPT2 HPT2 K1-PD K1 K1 K1 SSF3 HPT2 SSF3 SSF3 K1-PD SSF3 K1-PD K1-PD HPT2 GMAP_bG1 MTX MTX MTX MTX MTX MTX MTX MTX MTX MTX MTX MTX MTX GMAP_bG2 GMAP_bG2S1 Total Score GMAP_Man5 Similarity GMAP_Man678 GMAP_unk Safety CEX_AP Efficacy CEX_0K Productivity CEX_1K CEX_2K Unique CEX_unk Optimization Cell line development: Multifactorial selection of best clone aided by software tool focuses on quality Man3* Unk group bg0 (-N-F) Man 4 bg0 (-N) bg0 (-F) bg0 Man5 bg1(-n) bg1(-f) bg1 (1-6) bg1 (1-3) Man 6 unk5 unk6 bg2 Man 7 unk8 bg2s1 Man 8 All unk peaks 0% % % glycan structure 40% % 80% 100% Gmap GP2017 clones (SF500 FB screening) B Efficacy: half life Safety: ADCC Safety: CDC GMAP GMAP GMAP GMAP GMAP GMAP GMAP GMAP GMAP GMAP GMAP GMAP GMAP GMAP CEX CEX CEX bg0_f bg1_f bg0_n_f bg0_n bg1_n bg1_1_6 bg1_1_3 bg2 bg2s1 Man3 Man5 Man6 Man7 Man8 1K 2K AP Further optimization potential D Distance from design specification pool26/g418 K1-PD pool29/g418 K1-PD pool30/g418 K1-PD pool28/g418 K1-PD pool53/g418 HPT2 Weight = 0 K1-PD HPT2 SSF3 K1 HPT1 DG44 Profile in absolute scale pool26/g418 K1-PD pool29/g418 K1-PD pool30/g418 K1-PD pool28/g418 K1-PD pool53/g418 HPT2 Control QUALITY, growth, productivity, stability A SEC BP SEC AP Scoring rules C Ranking list CQA risk assessment MAb Knowledge base Software toolbox ARA 23 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

24 Total Score Cell line development: Multiple selection rounds required to hit the target 5.0 Individual Value Plot of Total Score P7 P Selected clone and backup clone for further process development Pools 50 ml 2. Clones 120 ml 3. Clones 1 L 4. Clones 5 L 5. Originator 24 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

25 Structural characterization The rituximab biosimilar example : Primary sequence Intact mab Mass and HC & LC by RP-HPLC-ESI-MS - comparable Amino acid sequence by RP-HPLC-ESI-MS/MS - identical RP-HPLC-UV/MS - comparable Free thiols by Ellman s assay - comparable Visser, J. et al., BioDrugs, May 2013 Reference product Reference product DS DP mass MS spectra of biosimilar mab and originator mab HC & LC 1,9 5,0 10,0 15,0 20,0 25,0 30,0 35,0 40,0 43,6 min Peptide map of biosimilar mab and originator - mab 25 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

26 Absorbance Units CD [mdeg/((g/l)cm))] Structural characterization The rituximab biosimilar example : Higher Order Structure CD, FTIR, HDX Circular Dichroism Spec. (near & far UV) - comparable Wavelength [nm] Reference product DP Reference product DP Wavelength [nm] FTIR Spec. comparable H/D Exchange comparable Reference product DP Wavenumber cm Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

27 Structural characterization The rituximab biosimilar example : SPR binding assays Surface Plasmon Resonance Fc-receptor binding assays Reference K D GP2013 K D FcRn µm µm Fc ϒ RIa nm nM Fc ϒ RIIa µm µm Fc ϒ RIIb µm µm Fc ϒ RIIIa F µm µm Fc ϒ RIIIa V µm µm Fc ϒ RIIIb µm µm Rituximab biosimilar (GP2013) is functionally indistinguishable from its reference product 27 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

29 Function: mabs possess multiple functions CDC complement dependent cytotoxicity C1 Membrane attack complex Target cell Target cell Fc g RIIIa PCD Effector cells (NK cells) ADCC Antibody dependent cellular cytotoxicity Programmed cell death ( apoptosis ) Blocking / Inhibiting RB Soluble Target 29 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June

30 ADCC (%of Reference) bg0(-f) [%] Cell line development case study: Minor glycan structures and ADCC bioactivity attention to detail is essential... Characterization of mab glycosylation heterogeneity High resolution identification and quantification of major (G0,G1,G2) and minor glycan structures (down to a level of 0.1 rel.%) 2x Targeting ADCC activity and fucosylation by clone selection bg0-f [rel. %] 30 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013 Originators Parental Cells Pool 18 Pool 16 Clone 19 30

31 In-vitro comparability: ADCC assays using clinical scale GP2013 (rituximab) drug product Daudi cell line & fresh effector cells SU-DHL4 & fresh effector cells Further cell lines tested: Raji Z138 ADCC comparable to MabThera / Rituxan 31 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

32 Structural characterization The rituximab biosimilar example : Bioassays Potency bioassays designed to give quantitative results Target binding ADCC CDC Apoptosis (n = 30 / 9) (n = 50 / 9) (n = 50 / 9) (n = 7 / 5) GP % % % % Reference range % % % % CDC complement dependent cytotoxicity C1 Effectorcell (NK cells) Membrane attack complex Target cell FcgRIIIa ADCC Antibody dependent cellular cytotoxicity Blocking PCD 32 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

33 In-vivo comparability: Two models for non-hodgkin s lymphoma SU-DHL-4 model Jeko-1 model Efficacy is similar 33 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

34 In-vivo comparability: PK following i.v. administration to primates Design Study groups: MabThera and GP2013, n=14 cyno. monkeys / group Dose Level: 5 mg / kg single i.v. infusion PK: AUC and C max are similar 34 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

35 B-cell Count [10 9 /L] In-vivo comparability: B-cell depletion following i.v. infusion Design Study groups: MabThera and GP2013, n= 14 cyno. monkeys / group Dose Level: 5 mg/kg i.v. administration 0,80 0,70 0,60 0,50 0,40 0,30 0,20 GP13 CD20 low MabThera CD20 low GP13 CD20 high MabThera CD20 high 0,10 0, Time [weeks] PD: B-cell depletion is similar 35 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

37 2 Goal of pre-clinical and clinical development is to confirm biosimilarity and not to prove de novo efficacy 6 12 m 9 12 m 2 4 yrs Time 1 Pre-clinic 2 PK/PD Ph I/II 3 Efficacy/Safety Ph III 4 Post-approval Abbreviated toxicology, efficacy/ safety in relevant species models Demonstrate PK/PD equivalence in a sensitive population - can be healthy volunteers Design tailored to demonstrate biosimilarity, but not patient benefit per se Sensitive indication Trial design might be different, e.g., endpoints Additional data to meet regulatory needs Key challenges are patient recruitment and reference supply 37 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

38 2 Clinical development requires strong scientific and operational capabilities Key success factors Know how to design innovative studies and negotiate with health authorities Patient recruitment supported by strong clinical networks & company credibility Strong clinical operations skills Desired outcome Example: Epoetin alfa Biosimilar (n = 60) Originator (n = 34) Weigang-Köhler et al. Onkologie 2009; 32: Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

39 ACR20 Response Rate [%] Clinical trials are not sensitive enough to differentiate different anti-tnf biologics Response Rates of anti-tnfs vary depending on study protocols ETA ADA DE019 IFX ATTRACT # CTZ RAPID 1 GLM GLM GO-FORWARD * * Weinblatt 1999 Weinblatt 2004 Maini 1999 Keystone 2008 Keystone FORWARD 2011 Week 12 (14*) Week 12 PLO Week 24 (30#) Week 24 PLO 39 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

40 SPR real time binding assay is much more sensitive to differentiating anti-tnfs and demonstrating biosimilarity Kaymakcalen, et al: Clinical Immunology, (2009) 131, Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

41 Focus of the clinical development program Confirm the similarity shown during the physicochemical, biological and nonclinical characterization in a clinical setting No need to show efficacy/safety de novo (has been established for the reference product) Requires sensitive setting to detect potential differences Select a sensitive model for the clinical trial Use of novel endpoints, biomarkers, and populations PK/PD studies in healthy volunteers may be more sensitive than trials in a disease area less confounding factors Healthy volunteers more responsive If a comparative (Phase 3) trial is needed, select an indication with a large effect size for the selected endpoint where immunogenicity can be reliably assessed which allows extrapolation to other indications 41 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013

42 SUMMARY Today, biologics can be thoroughly characterized and understood both structurally and functionally The goal posts for biosimilar development are set by the variability in the reference product and a thorough understanding of the molecule Using extensive cell line, process development, and analytical capabilities, biosimilars (including mabs) can be engineered to be highly similar Target-directed development provides safe and effective products A high level of structural and functional similarity lays the foundation for biosimilarity and should allow for a selective and targeted (pre)clinical approach and extrapolation of indications Biosimilar development relies upon and provides the thorough understanding of the pharmacological properties of biologics, and consequently their utility and applicability to development across scientific innovation. As such, they provide a platform for innovation at the scientific, technical, clinical, regulatory and pharmaceutical advance in health care. 42 Technological Innovation in Healthcare Biologics A. da Silva Brasilia, 26 June 2013