Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Neuropsychopharmacology wikipedia , lookup
Drug discovery wikipedia , lookup
Drug design wikipedia , lookup
Prescription costs wikipedia , lookup
Pharmaceutical industry wikipedia , lookup
Cell encapsulation wikipedia , lookup
Pharmacognosy wikipedia , lookup
Toxicodynamics wikipedia , lookup
Pharmacogenomics wikipedia , lookup
Neuropharmacology wikipedia , lookup
Dydrogesterone wikipedia , lookup
Pharmacokinetics wikipedia , lookup
APPLICATION OF PK/PD MODELING IN DRUG DEVELOPMENT Amarnath Sharma, Ph.D. Pfizer Global R & D Groton, CT Objectives of Early Drug Development Identification of critical risk factors prior to investment in full clinical development selection of better compounds Provide critical data to identify safe and effective dose and dose regimens more efficient development New Paradigm in Drug Development PK/PD in patients &/or in experimental models in healthy subjects (POM) PK/PD in dose-ranging proof of efficacy study in patients (POC) Confirm PD in the pivotal studies New Drug Application Post-marketing comparative PK/PD in patients Why Study PK/PD ? Characterize time course of pharmacologic response (therapeutic &/or toxic effects) Understand complex relationships – tolerance, sensitization, mechanistic delay Explain variability in response Identify biomarkers and validate surrogate endpoints Aid dose/dose regimen selection through simulation Bridge clinical efficacy and safety results across ethnic populations Bridge clinical results between adult and pediatric patients Requirements to Characterize PK/PD Relationship Validated biomarkers for therapeutic effects & toxicity – Should be meaningful (relates to MOA), reproducible, quantitative and allows frequent sampling to characterize the time course of effect – Validated Assay (reproducible, high precision….) – Exposure-response relationship Understanding of pharmacologic behavior of the drug and pathophysiology of the disease – Pharmacology and pharmacokinetic modeling Modeling Direct Responses Pharmacodynamics 1.0 Static Functions Related to Hill Equation 0.8 E = Eo ± S. CP Eq 1 E = Eo ± S. ln CP Eq 2 0.6 0.4 n max .Cp E E = Eo ± EC50 n + Cp n 0.2 E max .(Cp - CT ) = ± o E E ( EC50 - CT ) + (Cp - CT ) 0.0 0.001 0.01 0.1 1 10 100 Eq 3 Eq 4 1000 Concentration/EC50 Examples of direct PD effect with equilibration delay: CNS effects of benzodiazepines & anesthetics; Muscle Relaxants of d-tubocurarine Complexities in PK/PD Modeling Equilibration Mechanistic delay delay Tolerance Sensitization Active Drug metabolites interaction Modeling Indirect Responses Drug Examples: Anticoagulants effects of warfarin; Gene-mediated effects of corticosteroids kin Cp Vc ke Ce Biosignal R o kout CL Pharmacokinetics (equilibration delay) Cp = n Ai.e-li.t i =1 dCe = keo .(Cp - Ce ) dt Pharmacodynamics (mechanistic delay) dR = kin .H (t ) - kout .R dt dR = kin kout .H (t ).R dt Ro = kin / kout n E max .Ce H (t ) = 1±( ) n n EC50 + Ce Dayneka et al., JPB, 1993 Jusko et al., JPB, 1995 Sharma & Jusko, JPB, 1996 Sharma & Jusko, BJCP, 1998 Examples IL12: Tolerance in efficacy & safety biomarker response (IFNg). CD4 mAbs: Validate a safety biomarker in the preclinical transgenic mice model. IL5 mAb: Biomarker (eosinophil) is not a validated surrogate endpoint. P38 MAPK: Characterize an experimental model of acute inflammation for anti-TNF response. Avitriptan: Pop Characterize safety profile (BP and heart rate). PK/PD approach in Linezolid bridging program. IL12: An example of complex PK/PD relationship IL12 A 70 kDa heterodimer cytokine (35+40 kDa subunits). Enhances T helper 1-type immunity. Potentiates secretion of IFNg by, and the cytolytic activity of, NK cells and CTLs. IL12-induced secretion of IFNg is required for activity. mIL12 has potent antitumor& antimetastatic activity in murine tumor models. Under development for cancer and infectious diseases. Phase I Study Design Open label dose-escalation study in cancer patients. A single dose of rhIL12 followed by cycles of 5 consecutive daily iv injection at the same dose every 3 weeks. Days 1 MTD study 2 weeks washout 15 16 17 18 19 Repeat every 3 weeks of 500 ng/kg was established in this Atkins et al,Clin Cancer Res. 1997 Phase II Study Design Open label repeat-dose efficacy study in patients with advanced renal cell carcinoma. Cycles of 5 consecutive daily iv injection at MTD (500 ng/kg) dose every 3 weeks. Days 1 2 3 4 5 3 weeks washout 27 28 29 30 31 Repeat every 3 weeks Leonard et al., Blood, 1997 Phase II Study Results Treatment was associated with unexpected serious adverse events. Most of the patients experienced serious AEs after 2nd and 3rd doses. Two patients died and no one entered the 2nd cycle due to drug related toxicity such as GI bleeding. PK profiles for IL12 were comparable to those observed in Phase I study. Leonard et al., Blood, 1997 Reason for unexpected toxicity: A four-fold higher trough IFNg concentrations in Phase II may have caused the serious toxicity. Leonard et al., Blood, 1997 Summary If IFNg concentrations were used as a safety biomarker, it would have been possible to avoid serious AEs by stopping after 2nd dose in Phase II study. A single dose of IL12 causes tolerance in its ability to induce IFNg production upon further dosing. IL12 produces tolerance rapidly (3-4 days) during multiple dosing which lasts for a relatively long time period (14 days) in humans. PK/PD modeling to characterize schedule-dependent IL12-induced IFNg production is crucial for designing safe and effective dosing regimens. Comparative PD of Anti-CD4 mAbs in Transgenic Mice Sharma et al., JPET, 2000 Anti-CD4 mAbs Mediate their immunomodulatory effects via indirect response mechanisms: – removal of CD4+ T cells via effector mechanism; – down-modulation of cell surface CD4 via internalization or stripping and/or – inhibition of CD4-MHC II interactions. Under development for autoimmune disorder such as rheumatoid arthritis. Anti-CD4 mAbs Clenoliximab Keliximab Cynomolgus Macaque V-domain Human C l-domain VL VH VH VH VH CH1 C H1 V H H H CH2 CH2 Human g1 CH-domains VL VL CH3 CH3 • Primate/human chimeric CD4 mAb of IgG1 isotype. • Does not mediate complement dependent cytotoxicity. • Exhibits efficient binding to human IgG Fc receptors and can cause depletion of CD4+ cells. Pro Cys 227 Pro Ser Cys 230 VH VH CH1 CH1 H H CH2 CH2 CH3 CH3 V L Cynomolgus Macaque V-domain VH Human Cl-domain 235 Phe Leu Gly Gly Pro 240 Ser Glu Human g4 CH-domains • IgG4 derivative of Keliximab. • Does not mediate complement dependent cytotoxicity. • Does not exhibit efficient binding to human IgG Fc receptors. Reddy et al. J Immun, 2000 FcR and CD4 Mediated Cell Adhesion mAb Binding to FcR g (% Adhesion of THP-1 Cells) 25 20 Keliximab Keliximab Keliximab + sCD4 20 Clenoliximab Keliximab F(ab') 2 15 15 10 10 5 5 0 0 0.1 1 10 100 1000 0.1 1 10 100 1000 mAb (ng/mL) Reddy et al. J Immun, 2000 Study Design Male transgenic mice (n=10-13 per group) bearing human CD4 in place of the mouse CD4. Three dose levels (5, 25 & 125 mg/kg). PK: unbound plasma mAb concentrations. PD: CD4+ T cells; number of CD4 epitopes on the surface of T cells and CD8+ T cells. Preclinical Species Plasma Keliximab Concentration (ug/mL) Target-mediated Disposition 1000 hCD4+ Transgenic CD4 knock-out 1 mg/kg 1 mg/kg 10 mg/kg 30 mg/kg 100 10 1 Davis et al., Drug Metab Disp, 1996 0.1 0.01 0 20 40 60 80 Time (hours) 100 120 140 PK Model for Anti-CD4 mAbs Dose kPT Plasma (CP) Tissue (CT) V max . C P Km + CP dC p dt V max . C T Km + CT = - V max. C p Km+ Cp - k .C p PT dC T V max . C T = k .CpPT dt Km+ CT IC: Cp = Dose/Vc; CT = 0 Sharma et al., JPET, 2000 Mean Plasma Concentration (ng/mL) Pharmacokinetics of Anti-CD4 mAbs Clenoliximab 5mg/kg 25mg/kg 125mg/kg 1e+6 Keliximab 5mg/kg 25mg/kg 125mg/kg 1e+5 Parameter (unit) Estimate 890 Vmax (mg/mL/h) 1e+4 Km (ng/mL) 1e+3 5249 Vc (mL) 2.5 VT (mL) 25.6 kPT (day-1) 0.15 1e+2 0 100 200 300 TIME (hours) 400 500 Sharma et al., JPET, 2000 PD Model for Anti-CD4 mAbs koin kout CD4+ cell SC50 Smax dR dt = k in - k out . S(t) . R S max . Cp S(t) = 1 + SC 50 + Cp At a very high dose: Smax = (Ro - Rmax) / Rmax IC: Ro = kin/kout Sharma et al., JPET, 2000 Sharma & Jusko, Br J Clin Pharmaco, 1998 PK/PD of Anti-CD4 mAbs 60 Keliximab 60 5 mg/kg 25 mg/kg 125 mg/kg 40 40 20 20 Clenoliximab 25 mg/kg 125 mg/kg 0 0 0 400 800 1200 1600 0 400 800 1200 1600 Time (hour) Sharma et al., JPET, 2000 PD Parameters of Circulating CD4+ T Cell Number Treatment Keliximab Clenoliximab 0.035 (11%) 0.032 28.2 (18%) 16.2 SC50 (ng/mL) 37500 (54%) 419000 Ro (% lymphocytes) 34.1 (7.9%) 34.1 between-animal variability in R 13% (48%) 13% proportional residual error 29% (20%) 26% Kin (% lymphocytes/hr) Smax Variances Summary Clenoliximab is less potent and efficient than keliximab in causing depletion of circulating CD4+ T cells. The results of this study are similar to those from clinical trials at comparable doses. This study validates the transgenic mice as an appropriate model for preclinical PK/PD evaluation of anti-CD4 mAbs.