Transcript 0.5-1 year
Pharmaceutical Approaches to Antiviral Drug Discovery Peter S. Dragovich Pfizer Global Research and Development La Jolla Laboratories Drug Discovery/Development Pipeline • Multifaceted, complicated, lengthy process Today's Focus N HO OH HO OH N OH O O O O N OH OH N N N F O O- N H O N N OH O O F O NH2 O O H2N Products CO2H N N N NHCH3 N HN O S O O2S N N N N CF3 F Cl Cl Cl O Discovery O CH3O O N H O Exploratory Development Full Development NH2 Phase I 0 Idea Phase II 5 Phase III 10 12 -15 Years 15 Drug Drug Discovery Pipeline • Multifaceted, complicated, lengthy process • Up to 5 years to complete development transition Start Product Profiles Clinical Commercial TA Lead. 3-5 years Target Identification Virology Cell Biol. Lead generation Mol. Biol. Biochem. HT Screening HT Chem. Comp. Chem. Crystallog. Lead optimization Med. Chem. Res. Pharm. PDM Safety Process Chem. Dev. Patient/Product Profiles • Identify areas of high unmet medical need – Sub-optimal or no existing therapies • Identify differentiation basis for new therapy – potency/efficacy – resistance profile – dose size/frequency – safety/tolerability 0.01 0.1 1.0 Concentration (g/ml) 10.0 Lab objectives which address desired profiles Drug Discovery Pipeline Start Product Profiles 0.5-1 year Target Identification Lead generation Lead optimization • Biological entity associated with disease of interest (host or virus origin) • Appropriate modulation of target anticipated to impact disease in manner consistent with product profile Dev. Target Identification • Analyze virus life cycle • Identify critical points for intervention (host or virus origin) Host Cell 1. Entry Nucleus 2. Replication 4. Release 3. Assembly Target Identification Criteria • Activity/function essential for viral replication – Proven or inferred through biological experimentation • Drugable target (subjective!) – Known small molecule inhibitors – Well defined active (binding) site – Historical success against related targets • Conservation across virus variants (where applicable) • Selectivity vs human proteins Difficult to incorporate all criteria in single target Target Identification • Example: HIV Protease – Importance inferred from biology; proven through experimentation1,2 1 Pr55 gag 2 3 p17 p24 p1 4 p9 p6 6 5 Pr5160 gag-pol p17 p24 p1 TF 8 7 PR RT RN IN – Aspartyl protease Potent renin inhibitor examples O Large, lipophilic molecules O O OH H N S N H O OH N 1. Kohl, N. E.; et al. Proc. Natl. Acad. Sci. USA 1988, 85, 4686. 2. Kramer, R. A.; et al. Science 1986, 231, 1580. N H Ki <1 nM (human renin) Drug Discovery Pipeline Start Product Profiles 0.5-1 year Target Identification Lead generation Lead optimization • Identify molecule(s) which interact with chosen target • Biological properties attractive/promising but not ideal • Amenable to analog production Dev. Lead Generation • Need reliable and accurate biological assays – Routine production of target protein – Primary biochemical assay – Primary antiviral assay cpm incorporated 2000 1500 1000 500 0 0 – Secondary assays (counterscreens) 2 10 -6 -6 4 10 -6 6 10 -6 8 10 [inhibitor] moles/L 1 10 -5 1.2 10 -5 Lead Generation • Substrate/Ligand analogs – Biology or target mechanism must be known • Example: HIV RT nucleoside inhibitors O H3C NH N Deoxythymine HO DNA/RNA template O O substrate Synthesized DNA OH O H3C NH N AZT HO O • Incorporated into viral DNA by RT enzyme • Terminates synthesis (lacks 3'-hydroxyl) O AZT N3 Lead Generation • High-throughput screening – Large chemical archives (500K to 2MM compounds) – Miniaturization = improved cost-effectiveness Lead Generation • High-throughput screening – Allows for chance discovery of novel inhibitors • Example: HIV RT non-nucleoside inhibitors – Bind to allosteric site on enzyme surface – Disrupt enzyme structure/function F3C Cl O O N H Efavirenz Drug Discovery Pipeline Start Product Profiles 2-3 years Target Identification Lead generation Lead optimization Dev. • Prepare/synthesize analogs of leads • Improve biological properties • Optimized compound(s) suitable for clinical development Lead Optimization • Iterative process impacted by technology Combinatorial Chemistry Idea Generation Chemical Synthesis Biological Evaluation Biochemical assays Antiviral assays Met./abs./sol. assays Pharmacokinetics in vitro / in vivo Safety assessments Structure-based design Typical project progression Data Analysis Computational evaluation Development Candidate Future AV Discovery Needs • Continued understanding of patient and physician needs Product Profiles Start Target Identification Lead generation Lead optimization Dev Future AV Discovery Needs • Good understanding of patient and physician needs • Better understanding of virus biology – New target opportunities • Rapid identification of new viral diseases (SARS) • Improved association of viral infection with existing diseases Product Profiles Start Target Identification Lead generation Lead optimization Dev Future AV Discovery Needs • Improvements in drug discovery/development processes – Shorten timelines – Reduce attrition Lead optimization cycle times Safety predictions Clinical development times N HO OH HO OH N OH O O O O N OH OH N N N F O O- N H O N N OH O O F O NH2 O O H2N Products CO2H N N N NHCH3 N HN O S O O2S N N N N CF3 F Cl Cl Cl O Discovery O CH3O O N H O Exploratory Development Full Development NH2 Phase I 0 Idea Phase II 5 Phase III 10 12 -15 Years 15 Drug Summary • Antiviral drug discovery • Multifaceted, complicated, lengthy process • Application will lead to future antiviral therapies which address areas of high unmet medical need Start Product Profiles 3-5 years Target Identification Lead generation Lead optimization Dev. Acknowledgements Marc Deller Jay Davies Amy Patick Rich Michitsch Larry Truesdale