Principles of Clinical Pharmacology

1. Principles ofClinical Pharmacology Steven P. Stratton, Ph.D. 

2. Learning Objectives To define Pharmacokinetics & Pharmacodynamics To identify PK/PD approaches, terminology, and parameters To consider endpoints for PK/PD modeling To identify barriers and opportunities with molecularly targeted drugs To see new advances in clinical pharmacology To understand some practical considerations in design of PK studies in clinical protocols

3. Potential Therapeutic Outcomes Efficacy without toxicity Palliation Efficacy with toxicity Treatment, potentially curative Toxicity without efficacy Poison Neither toxicity nor efficacy Alternative medicine

4. Pharmacokinetics

5. Pharmacodynamics

6. Practical considerations in designing clinical drug intervention trials Why this drug? What dose? What schedule? What combination? What about other interactions?

7. Administering Drugs: Things to consider Age Renal status Liver function Polymorphisms Cytochrome P450 (genetics, drug interactions) Acetylator status (genetics) �Target� present?

8. Administering Drugs:Things to consider What should I measure? How do I measure it? Correct sampling schedule Validated method available?

9. Audience Question #1: Once in the clinic, what is the primary reason for failure of experimental drugs to gain FDA approval? Toxicity Efficacy Pharmacokinetic Properties Cost Marketing

11. PK Terminology

12. Audience Question #2: What is the most important pharmacokinetic variable? Volume of Distribution (Vd) Bioavailability (F) Clearance (CL) Half-life (t1/2) Area Under the Curve (AUC)

13. Apparent Volume of Distribution (Vd) The Vd is basically a convenient method for describing how well a drug is removed from the plasma and distributed to the tissues. However, it doesn't provide any specific information about where the drug is or whether it is concentrated in a particular organ. A large volume of distribution implies wide distribution, or extensive tissue binding, or both. Conversely, ionized drugs that are trapped in plasma, will have small volumes of distribution. The Vd is basically a convenient method for describing how well a drug is removed from the plasma and distributed to the tissues. However, it doesn't provide any specific information about where the drug is or whether it is concentrated in a particular organ. A large volume of distribution implies wide distribution, or extensive tissue binding, or both. Conversely, ionized drugs that are trapped in plasma, will have small volumes of distribution.

14. Protein Binding Large fraction of drug bound to tissue Unavailable for drug function Easily measured in vitro (% bound) Consequences What if bound drug is displaced? e.g. aspirin, warfarin displaces 1%

15. Clearance (CL)

16. Area Under the Curve (AUC)

17. Half-life (t�) Time required to clear 50% of drug Depends on Volume of Distribution (Vd) and Clearance (CL) Multi-phasic (if you can capture the distribution phase) Rule of Thumb: Drug is cleared in 5 half-lives

18. Other Important Parameters Peak plasma concentration Bioavailability Duration above a threshold concentration Free drug vs. total drug Cumulative dose Bioactivation to active metabolite

19. PK Analysis Linear Pharmacokinetics �First order� kinetics Covers most drugs Rate of change depends only on the current [drug] Half-life remains constant no matter how high the concentration AUC not affected by schedule Example: doxorubicin For example, the AUC after a 60 mg/m2 bolus dose of doxorubicin equals the total AUC for three daily (or weekly) bolus doses of 20 mg/m2, which equals the AUC for the same dose administered as a 96-hour infusion. A second implication is that the AUC is proportional to the dose. Thus, if one measures the AUC for a 60 mg/m2 dose, one can estimate the AUC for a 90 mg/m2dose in the same patient as being 50% higher.For example, the AUC after a 60 mg/m2 bolus dose of doxorubicin equals the total AUC for three daily (or weekly) bolus doses of 20 mg/m2, which equals the AUC for the same dose administered as a 96-hour infusion. A second implication is that the AUC is proportional to the dose. Thus, if one measures the AUC for a 60 mg/m2 dose, one can estimate the AUC for a 90 mg/m2dose in the same patient as being 50% higher.

20. PK Analysis Non-Linear Pharmacokinetics (�zero order�) Classic examples: ethanol, phenytoin Saturable metabolism Decreased CL at higher doses Shortened infusion ? increased AUC Examples: 5-FU, Taxol Saturable absorption Decreased proportional AUC at higher doses Lengthened infusion ? increased plasma conc. Examples: methotrexate, cisplatin This is clearly the case for 5-FU, probably due to saturation of its conversion to dihydrofluorouracil by the enzyme dihydropyrimidine dehydrogenase. 112 115 Schaaf et al. demonstrated that doubling of the 5-FU dose from approximately 7.5 mg/kg to 15 mg/kg (by IV bolus) resulted in a 135% increase in the mean AUC. 114 Since 5-FU is used on a variety of schedules, its nonlinear pharmacokinetic behavior may be one factor in its highly schedule-dependent effects. The opposite situation arises when a drug's absorption from the gastrointestinal tract (or renal tubular reabsorption) is saturable. In this case, an increase in dose results in a less than proportional increase in the AUC. Gastrointestinal absorption of drugs that resemble natural compounds is frequently mediated by active transport processes in the gastrointestinal tract that display saturable kinetics. Folate analogues such as MTX or leucovorin and amino acid analogues such as melphalan are examples of drugs with saturable absorption. 119 121 Cisplatin appears to have nonlinear pharmacokinetics due to saturation of its renal tubular reabsorption. 122, 123 Forastiere et al. demonstrated that free plasma platinum is increased by 42% when the drug is given as a 24-hour continuous infusion, rather than as a 20-minute infusion. 122 Prolonged infusion was also associated with a greater than three-fold increase in the free platinum half-life For saturable absorption, lengthening infusion of same amount of drug allows drug to �soak in�.This is clearly the case for 5-FU, probably due to saturation of its conversion to dihydrofluorouracil by the enzyme dihydropyrimidine dehydrogenase. 112 115 Schaaf et al. demonstrated that doubling of the 5-FU dose from approximately 7.5 mg/kg to 15 mg/kg (by IV bolus) resulted in a 135% increase in the mean AUC. 114 Since 5-FU is used on a variety of schedules, its nonlinear pharmacokinetic behavior may be one factor in its highly schedule-dependent effects. The opposite situation arises when a drug's absorption from the gastrointestinal tract (or renal tubular reabsorption) is saturable. In this case, an increase in dose results in a less than proportional increase in the AUC. Gastrointestinal absorption of drugs that resemble natural compounds is frequently mediated by active transport processes in the gastrointestinal tract that display saturable kinetics. Folate analogues such as MTX or leucovorin and amino acid analogues such as melphalan are examples of drugs with saturable absorption. 119 121 Cisplatin appears to have nonlinear pharmacokinetics due to saturation of its renal tubular reabsorption. 122, 123 Forastiere et al. demonstrated that free plasma platinum is increased by 42% when the drug is given as a 24-hour continuous infusion, rather than as a 20-minute infusion. 122 Prolonged infusion was also associated with a greater than three-fold increase in the free platinum half-life For saturable absorption, lengthening infusion of same amount of drug allows drug to �soak in�.

21. Audience Question #3: If you failed to abstain from one of these, but had to be at work and drug-free in one hour, which would be least likely to result in your dismissal? 5 mg oxycodone 150 mg erlotinib Top-shelf (Patron) margarita 4-5 bong hits Oxycodone linear PK, 3 hr half life Erlotinib linear PK at that dose, 36 hr half life Margarita gone in 1 hr (1 oz) Marijuana 24 hr half life (metabolites 45-60 day half life)Oxycodone linear PK, 3 hr half life Erlotinib linear PK at that dose, 36 hr half life Margarita gone in 1 hr (1 oz) Marijuana 24 hr half life (metabolites 45-60 day half life)

22. What is �Translational Research�?

23. Translational Research ��the interphase between basic research and its application in a clinical setting for the diagnosis, treatment, or prevention of a disease.� Dr. William Hait, Past Pres. AACR Observation ? Practice PK/PD is a cornerstone of translational research

24. PK/PD Modeling Preclinical animal data guides dose and schedule, but you still have to perform PK/PD in humans to confirm. PK/PD bridges from animal to manPreclinical animal data guides dose and schedule, but you still have to perform PK/PD in humans to confirm. PK/PD bridges from animal to man

25. PK Variability in Ovarian Cancer Patients250 mg/m2, 24 hr infusion, 22-23 hr sample, n = 48 Shows how important PK variability is in evaluating toxicitiesShows how important PK variability is in evaluating toxicities

26. PK/PD modeling of Taxol-induced neutropenia Non-linear kinetics Myelosuppression related to duration of threshold plasma concentration [Taxol] = 0.05 mM Prediction of disposition and toxicity Pharmacokinetic/pharmacodynamic relationship between duration spent at a plasma paclitaxel concentration > 0.05 pmol/L and percentage reduction in ANC in the first course of therapy. Symbols represent individuals treated at different doses and schedules (see Legend). Curve depicts the sigmoid Emax, model fit to the data. The broken portion of the curve represents that region for which data were not available. Neutropenia wasn�t really dose-dependent because of the variability in metabolism saturation (nonlinear PK). Instead, it was dependent on duration of plasma concentration > 0.05 uM.Pharmacokinetic/pharmacodynamic relationship between duration spent at a plasma paclitaxel concentration > 0.05 pmol/L and percentage reduction in ANC in the first course of therapy. Symbols represent individuals treated at different doses and schedules (see Legend). Curve depicts the sigmoid Emax, model fit to the data. The broken portion of the curve represents that region for which data were not available. Neutropenia wasn�t really dose-dependent because of the variability in metabolism saturation (nonlinear PK). Instead, it was dependent on duration of plasma concentration > 0.05 uM.

27. PK/PD ModelingEffect of formulation on paclitaxel PK First-Order Elimination (Abraxane) Rate of elimination is proportional to drug concentration Constant fraction of drug eliminated per unit time Zero-Order Elimination (Taxol) Rate of elimination constant regardless of drug concentration Constant amount of drug eliminated per unit time Abraxane has linear PK because no cremaphor Taxol is zero order elimination meaning potential major increases in toxicity with small increases in doseAbraxane has linear PK because no cremaphor Taxol is zero order elimination meaning potential major increases in toxicity with small increases in dose

28. paclitaxel (ABI_007) nanoparticles 30 min infusion, q 21d No cremaphor No premeds Linear kinetics Clin Cancer Res 8:1038-1044 (2002) paclitaxel (Taxol) 6 hr infusion, q 21d Cremaphor formulation Premedication Non-linear kinetics J Clin Oncology 9:1261-1267 (1991) Take home message- difficult to predict tox with non-lin kineticsTake home message- difficult to predict tox with non-lin kinetics

29. PD Modeling Example: Pharmacogenetics  Myelotoxicity and UGT genetic polymorphisms Irinotecan 350 mg/m2 90 min infusion, q3w n = 66 SN-38 metabolism dependent on UGT variant Identification of patients predisposed to severe irinotecan toxicity Most Pts have low risk of Grade 4 neutropenia on irinotecan, but Pts with 7/7 genotype have 50% incidence of Grade 4 neutropenia.Most Pts have low risk of Grade 4 neutropenia on irinotecan, but Pts with 7/7 genotype have 50% incidence of Grade 4 neutropenia.

30. Molecularly-targeted Drugs

31. Shift Towards Target-based vs. Compound-based Development Compound-based (backward) Interesting compound discovered with activity in in vitro models Target-based (forward) Protein or gene targets identified on carcinogenesis pathway. Drugs designed to interfere with these specific targets

32. EGFR as a Molecular Target Member of erbB family of receptor tyrosine kinases EGFR (ErbB1), HER2/Neu (ErbB2), HER3 (ErbB3) and HER4 (ErbB4) Overexpressed in various solid tumors Overexpression has been correlated with poor prognosis EGFR signaling is implicated in angiogenesis, proliferation, and inhibition of apoptosis

33. EGFR Mechanism

34. EGFR Targeted Therapy Neutralizing monoclonal antibody cetuximab competitive inhibitor prevents dimerization Tyrosine kinase inhibitors erlotinib, gefitinib reversible inhibitors lapatinib duel EGFR/erbB2 irreversible inhibitor Erlotinib clearance doubles in smokers Gefitinib limited access only since 2005 Lapatinib approved in 2007 w/ capecitabine erb2 exp adv breast caErlotinib clearance doubles in smokers Gefitinib limited access only since 2005 Lapatinib approved in 2007 w/ capecitabine erb2 exp adv breast ca

35. Issues with molecularly targeted EGFR inhibitors Mutation in EGFR Activation of redundant pathways Constitutive activation of downstream signaling factors Ligand-independent activation of EGFR

36. Altered response to EGFR inhibitors EGFR mutations have been characterized in gliomas, NSCLC, breast, ovarian cancers Activating mutations correlated with increased response to gefitinib in NSCLC

37. Resistance to EGFR inhibitors Resistance caused by activation of other tyrosine kinase receptors that bypass the EGFR pathway

38. Resistance to EGFR inhibitors

39. Resistance to EGFR inhibitors EGFR can be activated by integrins cetuximab could not inhibit this pathway

40. Concerns with Targeted Therapy �The Butterfly effect� Predicting toxicities of a single target is difficult when the target of interest is relatively upstream in a pathway Example: bortezomib (Velcade) ? myelosuppression, fatigue, etc. Dosing regimens are difficult to determine High potency ? difficult detection of drug Cytostatic mechanism ? low toxicity, MED vs. MTD Targeted therapies are not as �specific� as we think (e.g., imatinib mesylate, sorafenib) Pleiotropism

41. Concerns with Targeted Therapy (cont�d) Redundancy Cells that �find a way� get rewarded and select for resistance Delivery (chemistry) The drug may not reach the target in vivo (PK) Bogus mechanism Almost all in vitro mechanisms are convenient to believe once the xenograft data is positive A good (valid) biomarker is hard to find

42. How do we improve targeted therapies? Combinations We need better tools to select the best patient/therapy combinations

43. Pharmacogenomics How variations in the genome affect the response to medications

44. Personalized therapy in ovarian cancer: A genomic approach Dressman et al, JCO 25:517 (2007) Primary ovarian tumors collected at surgery from 119 patients All patients rec�d platinum-based therapy 85 CR, 34 IR DNA microarray analysis Gene expression signatures used to predict oncogenic pathways activated in a tumor Relationship between pathway activation and survival was analyzed in CRs and IRs 84 Complete Response, 34 Incomplete response 84 Complete Response, 34 Incomplete response

46. How is this helpful? Is it real? Potential (very cool) application of pathway prediction in this patient population

47. Practical Advice in PK Study Design

48. Patients should not be made to feel that the situation is out of their control. Be aware of all regulations (HIPAA, others) regarding collection, storage, and use of collected blood and tissue.Patients should not be made to feel that the situation is out of their control. Be aware of all regulations (HIPAA, others) regarding collection, storage, and use of collected blood and tissue.

49. Typical Phase 1/PK Study Goal Capture adequate tissue samples to measure drug/metabolite levels over time 0, �, 1, 2, 4, 8, 24, 48 hr Day 8, Day 15 Capture 4-5 half-lives if possible May need to collect urine, other fluids?

50. Know your analyst Ensure that the analytical technique is available Ensure that the method is available, validated, and reliable Define sample preparation Know your sample size The biometrist is your friend visit them early and often Be kind to nurses Do you really want that 16 hr PK? Don�t require a sample at the end of the infusion- too many things at once is trouble

51. Consider your patients Don�t exsanguinate them Extended PK sampling can be exhausting Don�t sample from the infusion port Define and monitor sample handling!! Ensure study personnel are informed and understand SOPs Shipping whole blood at room temp instead of frozen plasma ? Disaster Cheap ink, cheap labels, and freezers don�t mix

53. Compound-based vs. Target-based Drug Development