Approaching the In Silico Child Jeffrey S. Barrett, PhD, FCP

1. Approaching the In Silico Child Jeffrey S. Barrett, PhD, FCP

2. Outline • Background • Pediatric Pharmacotherapy Defined • What’s missing? • Pediatric Priors – where do they come from? • Models for understanding vs prediction • The EMR -- leveraging hospital informatics • The Pediatrics Knowledgebase (PKB) Project • Design Issues • Methotrexate Drug Dashboard • Vision for the Future

3. Pharmacotherapy • Principally concerned with the safe and effectivemanagement of drug administration. • Implies an understanding of pharmacokinetics (PK) and pharmacodynamics (PD) so that individual dosing guidance, when necessary, can be provided to optimize patient response within their individual therapeutic window.

4. Pharmacotherapy • 75% prescription drugs in children “off-label” • Usage not described in package insert • Approved indications • Adequate controlled studies • Consequences of off label usage • Benefit, No effect, Harm

5. Pharmacotherapy • Unapproved is not improper • Decision based on safety/efficacy data • Medical literature vs Regulatory Guidance • “Best medical judgment”

6. PharmacotherapyThe Landscape for Predicting Exposure Active/inactive metabolites Urine, Feces, Expired Air ABSORPTION - Site (i.e., GIT, skin, tissue depot) - First-pass effect (oral) - Drug properties (i.e., solubility) METABOLISM ELIMINATION • Pathway(s) • Sites (GIT, liver, lung) - Unchanged drug - Metabolites Excretory Sites Distribution in Blood Cells Bound to plasma proteins Free Drug in Plasma or Extracellular Fluid SITE(S) FOR THERAPEUTIC EFFECT(S) Pharmacologic Activity DISTRIBUTION - Sites (Tissues, fat, etc) - Binding SITE(S) FOR TOXIC EFFECT(S) Toxic Activity

7. PharmacotherapyWhat’s Missing? • Drug disposition in children is best described using the term “variable” • In general, variability is much greater in first 3 months of life and declines to “adult variability” • Estimating exposure is challenging due to developmental changes affecting absorption, distributionandbiotransformation • Exposure also function of exogenous influences (diet, concurrent illness) J. Steven Leeder, Pharm.D., Ph.D.

8. PharmacotherapyWhat’s Missing? • “Scaling” pediatric from adult dosing data needs to take into consideration: • Knowledge of relative contribution of ADME components at each developmental stage • For biotransformation, knowledge of fractional contribution of each pathway to total CL • Isoform-specific patterns of development • Interindividual variability in the rate and pattern of pathway development • Age-dependent differences in population variability J. Steven Leeder, Pharm.D., Ph.D.

9. Pediatric PriorsAbsorption J. Steven Leeder, Pharm.D., Ph.D.

10. Pediatric Priors Distribution Intracellular Water Protein Fat Other Extracellular Water Premature Newborn 4 mos 12 mos 24 mos 36 mos Adult 20 100 0 40 60 80 Percentage of Total Body Weight

11. Pediatric Priors Metabolism • Functional drug biotransformation capacity acquired in isoform-specific patterns • Onset in Days: CYPs 2C9, 2D6, 2E1; UGTs 1A and 2B7? • Onset in Weeks: CYP3A4 • Onset in Months: CYP1A2 • Onset in Years: FMO3 J. Steven Leeder, Pharm.D., Ph.D.

12. Pediatric Priors Metabolism • Time to activity “peaks” also isoform-dependent, but less well characterized • In general, in vitro studies indicate that variability is much greater in first 3 months of life and declines to “adult variability” • Newborns at particularly high risk for concentration-dependent toxicity due to developmentally delayed drug metabolism (e.g. chloramphenicol, SSRIs) J. Steven Leeder, Pharm.D., Ph.D.

13. Pediatric PriorsMetabolism Liver Mass:Body Weight Change with Age Liver Mass (% Body Weight) Age (years) J. Steven Leeder, Pharm.D., Ph.D.

14. Pediatric Priors Metabolism Activity Newborn Toddler Puberty Adult J. Steven Leeder, Pharm.D., Ph.D.

15. Pediatric Priors Models for Understanding vs Prediction MODEL IMPACT INFORMATION CONTENT • Discovery • Define functional relationships • PK/PD Data signature • Early CUI • Decision-making • Candidate screening / selection • Dose selection • Study designs • Compound progression • Patient Pharmacotherapy • Dosing guidance • Patient management of AE / ADRs • Optimize sub-therapeutic response • Rescue therapy Discovery Decision- Making Pharmacotherapy

16. STATA WinSAAM Epidemiologic Analysis X2 X3 X1 Database Development Diagnostic Analysis Database -0.2 0.6 Jet Engine -0.1 0.1 0.7 0.5 AKA Intermediate Processing Data Fitting and Fit Analysis Data Dict. Publications and Presentations Excel 0.1 -0.2 SAAM Charts Reports Y Pediatric Priors Tools for Prediction PLASMA FLOW PLASMA HEART HEPATIC ARTERY SPLEEN LIVER BILE KIDNEY URINE BONE MARROW MUSCLE CARCASS

17. Pediatric Priors Electronic Medical Records • Paper-based records have been in existence for centuries and their gradual replacement by computer-based records has been slowly underway for over 20 years. • The penetration of electronic medical records (EMRs) may have reached over 90% in primary care practices in Norway, Sweden and Denmark (2003), but has been limited to 17% of physician office practices in the USA (2001-2003). • The EMR systems that have been implemented have been used primarily for administrative rather than clinical purposes.

18. Electronic Medical Records CHOP Environment • EpicCare and EpicWeb – ambulatory computerized medical record. • Sunrise Clinical Manager – impatient clinical order entry, charting, charging, and documentation. • Wellsoft – Emergency Department patient management, clinical documentation, and reporting. • ChartMaxx – legal medical record for impatient, emergency, ambulatory surgery. • IDX Rad – radiology patient management and transcription. • Meditech – laboratory information system

19. Pediatric Knowledgebase (PKB)Concept • A physician-designed informatics system which surfaces the “most relevant” data to guide individual patient pharmacotherapy • Construction of individual “drug dashboards” which provide quantitative prediction (as requested) relative to historical and comparative patient metrics.

20. Pediatric Knowledgebase (PKB)Project Aims • Provide dosing guidance consistent with formulary standard of care, • Examine patient pharmacotherapeutic indices relative to historical controls derived from the hospital data warehouse, • Explore treatment – diagnoses – drug correlation in conjunction with utilization and • Educate physicians on clinical pharmacologic principles specific to population and drug combinations of interest.

21. Pediatric Knowledgebase (PKB)Design Issues Project Design Requirements Gathering Project Scoping Charter, IRB Training Steering Committee Formation, Prioritization Design Team: Physician champion for therapeutic area, Clinical Pharmacologist / Modeler, Programmer, IT specialist Dashboard Prototype Development Forecasting DSS Data Warehouse Access, Security, Modeling PKB Shell SCM Interface User Interface Formulary Metrics Questionnaire Clinical and operational benefit Steering Committee: Clinical Care Attending (Chair), Members: IRB head, external pharmacometrician, 3 physicians, project sponsor, IT specialist, business manager, hospital pharmacist Testing Presentation to Therapeutic Standards Committee (TSC) TSC: Approval for “production use” granted by Therapeutic Standards Committee Refinement Training and Implementation

22. Pediatric Knowledgebase (PKB)Design Issues - Source Data

23. Pediatric Knowledgebase (PKB)Design Issues – Static Data

24. Pediatric Knowledgebase (PKB)Design Issues – Hospital Computing Environment

25. Methotrexate Dashboard • Anti-folate chemotherapeutic agent • Renal excretion • Enterohepatic recirculation • Toxicity at high or prolonged low exposure

26. Methotrexate Dashboard

27. Methotrexate Dashboard • Dose? • Dose adjustment? • Therapeutic drug monitoring? • Toxicity?

28. Methotrexate Dashboard • 12 year-old boy with osteosarcoma and renal insufficiency…. • 3 year-old girl with leukemia and previous history of hyperbilirubinemia….

29. Percentage of patients with elevated creatinine able to get full dose without toxicity…. Most common toxicity in patients with elevated creatinine…. Methotrexate Dashboard

30. Methotrexate Dashboard

31. Methotrexate Dashboard • Underlying model accounts for combined elements of methotrexate therapy • Dose characteristics (amount, duration) • Covariates (age, weight, gender, disease state, etc.) • Pharmacokinetics (plasma concentration) • Pharmacodynamics (creatinine clearance) • Applied to individual patient data for TDM

32. Methotrexate Dashboard Dose, infusion time Central Compartment Peripheral Compartment Dissipation of Effect Effect Compartment Elimination from Plasma

33. Current MTX data model: Patients with normal renal function Patients with compromised renal function Very young patients (3 month to 1 year old) Methotrexate Dashboard

34. Methotrexate Dashboard • Provide predictions of: • MTX concentrations at later time • Creatinine clearance at later time • Time to reach threshold plasma concentration • Guidance for dose titration • Diagnosis of delayed MTX clearance due to acute nephrotoxicity • Guidance of rescue therapy in response to renal toxicity

35. Methotrexate Dashboard

36. Methotrexate Dashboard

37. Methotrexate Dashboard

38. Methotrexate Dashboard

39. Methotrexate Dashboard

40. Methotrexate Dashboard

41. The PKB Team Mahesh Narayan Sundarajaran Vijakumar, PhD Kalpana Vijakumar Mark Schreiner, MD Rollie Essex Arun Muralidharan Santhanam Srinivasa Raghavan Theo Zaoutis, MD Athena Zuppa, MD Jeffrey Skolnik, MD John Mondick, PhD Kelly Wade, MD Peter C. Adamson, MD Garret Brodeur, MD Manish Gupta, PhD Di Wu, PhD Bhuvana Jayaraman Dimple Patel Dominique Paccaly, PharmD

42. Questions?