Current Status: CPTR PBPK Modelling Effort. Lisa Almond Translational Science (DMPK) Simcyp Limited (a Certara Company)

Transcription

1 Current Status: CPTR PBPK Modelling Effort Lisa Almond Translational Science (DMPK) Simcyp Limited (a Certara Company)

2 Project Objectives To develop an exploratory PBPK model for predicting drug distribution of model drugs to the lungs. The ultimate purpose of the model is to aid design of dosage regimens of anti-tb drugs that provide optimal concentrations of drug at the target site of action, when drugs are dosed in combination.

3 Overview of Presentation Background & the PBPK Approach Virtual South African Population Overview of Mechanistic Lung Model Simulated Concentration-time profiles of anti-tb drugs Current Status & Future Directions

4 IVIVE-PBPK Linked Models Venous Arterial Applications in TB Drug Development/ Management Lung Inter individual variability within a specific population Generic Investigation of special populations ethnic groups/ disease groups/ paediatrics/ genotypes-phenotypes Investigation of drug penetration to the active site Adipose Bone Brain Heart Kidney Muscle Hypothesis testing (e.g. elucidation of mechanisms) Portal Vein IV Skin Liver EHC Spleen Pancreas Gut PO Investigation of DDIs & optimal drug combinations (the effect on systemic and local concentrations) Clinical trial design FIH predictions

5 Regulatory Acceptance of PBPK e.g. DDI Predictions over the last decade: Proof of concept Increased knowledge/understanding Increased model complexity (static to dynamic), Validation/best practice Regulatory acceptance Routine use across industry Labelling PBPK Modelling on impact Product on clinical Labelling use (label wording) ibrutinib (Janssen) macitentan (Actelion) simprenavir (Janssen) Sinha et al., 2014 [Enter Presentation Title in Insert Tab > Header & Footer 5

6 Frequency Frequency Systems (Bottom-Up) Approach Frequency Systems Data Drug Data Trial Design Age DISTRIBUTION Weight of physiological Tissue Volumes parameters Tissue Composition Age Cardiac Output Tissue Flows [Plasma Protein] Size of Liver MW LogP pka Protein binding BP ratio In vitro Metabolism Permeability Solubility Dose Administration route Frequency Co-administered drugs Populations Size of Lungs Mechanistic IVIVE linked PBPK models Prediction of drug PK (PD) AND associated variability in population of interest Jamei et al., DMPK, 2009, Rostami-Hodjegan, CPT, 2012

7 Height (cm) South African Population Age-Distribution Age-Height 200 Height-Weight Demographics Body size Age (y) Observed CYP3A5 NAT-2 Body Surface Area Nwoye model Observed SLOW PM EM Genetics Albumin INTERMEDIATE FAST Haematocrit Male Observed

8 Physiology changes in TB BMI Weight AAG Lung ph Albumin Haematocrit Healthy TB-infected Male

9 FO/ADAM Venous Arterial PBPK Model Lung Generic Adipose Bone Predicted tissue/plasma partition coefficients- P t:p Rodgers & Rowland, J Pharm Sci 2005, 2006 Age + Tissue volumes Gender Weight Height Brain Heart Adipose Brain Bone Spleen Erythrocytes Plasma Kidney Muscle Gut Heart Kidney Liver Lung Muscle Skin Permeability limited lung model Skin Liver Spleen Alveoli Low RLA Right lung Middle RMA Top RTA Left lung Low LLA Top LTA Lower airway LAA Upper airway UAA Inhaled dose Portal Vein Pancreas Fluid RLF RMF RTF LLF LTF LAF UAF IV EHC Gut PO Mass RLM RLB RMM RM B RTM RTB LLM LLB LTM LTB LAM LAB UA M UAB Pulmonary Reservoir (PBR) GI tract Venous Arterial

10 PBPK Model FO/ADAM Permeability limited lung model e.g. Drug X Low Right lung Middle Top Low Left lung Top Lower airway Upper airway Inhaled dose Plasma Conc. e.g. 10 virtual clinical trials Alveoli RLA RMA RTA LLA LTA LAA UAA Fluid RLF RMF RTF LLF LTF LAF UAF Mass RLM RMM RTM LLM LTM LAM UAM RLB RMB RTB LLB LTB LAB UAB Venous Pulmonary Reservoir (PBR) Arterial GI tract ELF Conc. e.g. 10 virtual clinical trials ELF:Plasma e.g. 10 virtual clinical trials Concentrations in each segment can be linked to PD ELF - Epithelial Lining Fluid

11 Simulation of PK for anti-tb drugs Pyrazinamide Agrawal et al., 2002 Ethambutol NAT-2 Peloquin et al., 1999a SLOW INTERMEDIATE FAST Rifampicin Goutelle et al., 2009 Isoniazid Peloquin et al., 1999b

12 Observed and Simulated ELF: Plasma Without any active transport; assuming ELF ph 6.6, fu fluid = 1, fu cell = predicted

13 PBPK Model FO/ADAM Permeability limited lung model e.g. Drug X Low Right lung Middle Top Low Left lung Top Lower airway Upper airway Inhaled dose Plasma Conc. e.g. 10 virtual clinical trials Alveoli RLA RMA RTA LLA LTA LAA UAA Fluid RLF RMF RTF LLF LTF LAF UAF Mass RLM RMM RTM LLM LTM LAM UAM RLB RMB RTB LLB LTB LAB UAB Venous Pulmonary Reservoir (PBR) Arterial GI tract ELF Conc. e.g. 10 virtual clinical trials ELF:Plasma e.g. 10 virtual clinical trials? Dartois et al., 2014 ELF - Epithelial Lining Fluid

14 Current Status & Future Directions Progress to date Simulate plasma and ELF concentrations of multiple anti-tb drugs administered simultaneously using a combination of in vitro and in vivo data. 7 examples investigated so far. Reasonable agreement to observed for some compounds. Some compounds require active transport component to recover the observed ratio. Use the model to help elucidate mechanisms of penetration into ELF. What do we want to simulate ultimately? Prospective prediction of ELF & granuloma concentrations based purely on in vitro/physicochemical data. Predict concentration gradients across granulomas/lesions What are the current knowledge gaps? The drivers of penetration into granulomas (and distribution within granulomas) are uncertain. Can this be linked to drug properties such as physchem properties, affinity for active transport, binding etc? Needed for prospective prediction. Models can be expanded as the science and data evolve.

15 Acknowledgements Simcyp Iain Gardner Gaohua Lu Masoud Jamei Ben Small Shriram Pathak Janak Wedagedera C-Path Institute Klaus Romero Chris Hanson Nandini Konar Members of the M&S WG [Enter Presentation Title in Insert Tab > Header & Footer 15