A rational approach to drug interactions during drug development

1. A rational approach to drug interactions during drug development Steve Warrington

2. Outline • impact of drug interactions on a drug’s future • review of mechanisms of drug interactions • approach to rational selection of interaction studies • approaches to study design • new methods of obtaining drug interaction data

3. Why need we be concerned? • clinically significant drug interactions are infrequent BUT • can be very serious when they occur

4. A cautionary tale - 1 “ We are taking this action based on evolving information about drug interactions.” “In principle, drug interactions can be satisfactorily addressed by appropriate product information; however with respect to Posicor, we believe that the complexity of such prescribing information would lead to difficulties in use.” moral – you can’t trust the doctors (or the patients)

5. A cautionary tale - 2 Brovavir • anti-herpetic antiviral • licensed only in Japan • known inhibitor of 5-fluorouracil metabolism • contraindicated with 5-FU • drug withdrawn after >10 deaths due to 5-FU toxicity • moral – you can’t trust the doctors,even in Japan

6. A cautionary tale - 3 • terfenadine – erythromycin • fatal cardiac arrhythmias due to accumulation of terfenadine when its metabolism is inhibited by erythromycin • cyclosporin – ketoconazole • cyclosporin levels rise when ketoconazole inhibits its metabolism • damages transplanted kidney

7. A cautionary tale - 4 • do we err on the side of caution? Perhaps not – • duty of regulators to protect the public • the regulators can’t trust the doctors • the doctors can’t trust the patients • multiple names for the same product means patients (but not doctors) can be forgiven for being confused • pharma companies fear massive liabilities, so withdraw drugs from market too readily (IMHO)

8. Mechanisms • pharmacokinetic • absorption - distribution - elimination • pharmacodynamic but • most important drug interactions occur by • inhibition of elimination, or • pharmacodynamic interaction • increased drug concentration or effect is usually worse than decreased(few drugs are actually keeping the recipients alive) • how can we predict which drugs are likely to interact?

9. Absorption • may be predictable from physicochemical properties • solubility • pH dependence of solubility • pH dependence of stability • extent of absorption usually affects response • rate of absorption may affect response

10. Absorption interaction example FPV has pH-dependent solubility: maximum at pH 3.3, reduced at higher pH. Phosphate group on FPV could bind metal cations in antacid, either altering solubility or preventing presystemic conversion of FPV to APV. Median plasma APV concentration after single-dose of 1,400 mg FPV alone, or plus 30 mL MAALOX TC, or 1 h after 300 mg ranitidine (n=26 per group) Antimicrob Agents Chemother. 2005 January; 49: 467–469.

11. Distribution interactions one drug affects rate and extent of another drug’s access to tissues / cells Plasma protein binding Transporters potentially clinically important clinically unimportant usually

12. Protein binding - 1 • displacement from plasma or tissue binding sites • importance of plasma protein binding displacement (PPBD) is misunderstood • PPBD alone usually leads only to a temporary & modest increase in free drug concentration & effect • clinically significant interactions ascribed to PPBD • warfarin - phenylbutazone • tolbutamide - sulphonamides have involved inhibition of metabolism in addition to PPBD

13. f u fraction unbound 0.1 0.2 0.2 0.2 Suddenaddition of a displacer, eg valproate Displacement of phenytoin by valproate

14. Protein binding - 2 • drugs most likely to show altered clinical response due to PPBD • >90% protein bound • small distribution volume • narrow therapeutic index • warfarin, phenytoin, tolbutamide • or high hepatic extraction drugs when given iv • although PPBD rarely causes clinical effects, it’s important to know about it when measuring and interpreting plasma drug levels • for further reading see Rolan PE. Br J Clin Pharmac 1994;37:125–128

15. Transporter interactions • many drugs cross cell membranes poorly • many drugs are actively pumped in and out of cells • transporter interaction can affect elimination • eg penicillin - probenecid • transporter interaction in organ of effect or toxicity; or if intracellular access is required for drug action • inhibiting transporters may affect safety or efficacy • without necessarily affecting plasma PK • hence transporter interactions can cause • distribution interactions • clearance interactions – by reducing access to eliminating organ, eg liver • excretion interactions – by reducing access to kidney

16. Transporters: P-glycoprotein • confusing nomenclature: P-glycoprotein (Pgp) = MultiDrugResistance (MDR) 1 + ABCB1 (anion binding cassette B1) • PgP pumps drugs out of cells • increased PgP activity → decreased efficacy of anticancer drugs, so is a drug target • PgP determines digoxin distribution & clearance • hence multiple level interactions with verapamil • PgP → major activity at Blood Brain Barrier (pumps drugs out of brain) so can affect central–peripheral balance of opioid effect

17. Metabolism interactions • Cytochrome P450 isoenzymes (CYP) • known inhibitors of each isoform • known inducibility of isoforms • purified human isozymes available for in vitro testing • can predict CYPs that metabolise new drug • can test in vitro if new drug inhibits CYP • in vitro screening can identify potential interactions & eliminate others • problem extrapolating in vitro concentration-effect relationships to in vivo • can test if new drug metabolism inhibited by known inhibitors • see http://medicine.iupui.edu/flockhart/table.htm

18. Importance of CYPs for drug metabolism 3A4 highly variable activity inducible no genetic polymorphisms 2D6 - metabolises many CNS drugs - non-inducible enzyme - poor metaboliser genotype - codeine, tramadol, metoprolol, desipramine

19. Metabolism inhibitors – traps for the unwary • just because a drug isnot metabolised by a pathway doesn’t mean that it’s not an inducer or inhibitor of that pathway • if a drugis metabolised by a pathway, that doesn’t mean that it is an inhibitor or inducer of that pathway • interaction isn’t all or none: depends on • concentration of inhibitor relative to its potency • extent of alternative pathways of elimination • does NOT generally depend on concentration of substrate drug

20. Double-effect for high first-pass drugs Inhibition of metabolism increases blood levels by: • reducing first-pass effect AND • by reducing clearance NB both effects will increase in bioavailability, because both effects will increase AUC and Cmax

21. Double-effect example

22. Consequences of inhibiting a pathway • if pathway is the major route, blood levels go up in proportion to blockade of pathway • beware of blocking a ‘non-major’ pathway if an alternative pathway could be deficient • deficiency in CYP 2D6 is most common cause of trouble

23. Renal interactions • unlikely for drugs which are purely filtered • possible for drugs which are actively secreted or reabsorbed • separate active transport systems each with own inhibitors • probenecid (negatively charged drugs) • cimetidine (positively charged drugs) • PgP as well

24. Food components • grapefruit juice inhibits CYP3A4 • responsible component not clear ?bergamottin • other (citrus) fruits have smaller effect • St John’s wort (hypericin) • herbal treatment for depression • CYP3A4 inducer • failure of anti HIV therapy • rejection of transplanted kidney

25. Pharmacodynamic interactions • likely when • two drugs act on same receptor system • two drugs produce similar effects (desired or undesired) • can be alteration of intensity of effect • additive • alcohol & sedatives • antagonistic • β-blockers & β-agonists • new effect • eg serotonin syndrome • combination of triptans with SSRI or SSNR • MAOI with SSRI • pethidine with SSRI

26. Beneficial interactions • ritonavir boosts levels of protease inhibitors eg saquinavir (saves money & tablets) • probenecid allows single dose amoxicillin treatment of gonorrhoea (ensures compliance) • inhibitors of CYP 3A4 & PgP (diltiazem, verapamil, ketoconazole) boost levels of cyclosporine (saves money)

27. Factors that determine how much interaction data are required 1 • how well do we understand the processes controlling absorption, distribution, metabolism and elimination of the drug? • less understanding means more drug interactions possible so more data required • is drug in class known to be interaction-prone? • eg imidazoles, anticonvulsants • what is the therapeutic index of the drug ? • if low, more interaction data required

28. Factors that determine how much interaction data are required 2 • is drug likely to be given as combination therapy? • if yes, more data required • is drug likely to be given with a drug of low therapeutic index ? • eg digoxin, warfarin • is drug likely to be given to the elderly or other groups using much chronic medication? • if yes, more data required • does the drug have CNS effects ? • alcohol interaction study needed

29. What type of data is required ? In vitro • protein binding • if no displacement, no in vivo data required • if displacement, human data may be required • metabolism studies • CYP inhibition by test drug • CYP responsible for test drug metabolism Specific human study • classical clinical pharmacology • using a likely coadministered drug • using ‘probes’ Population approach • observational

30. Specific studies – ‘interactors’ and ‘victims • first decide on ‘interactors’ and ‘victims’ • ‘interactor’ • drug which causes the interaction – the ‘perpetrator’ • ‘victim’ • drug whose concentration or effect is changed • eg warfarin is always a victim never an interactor • but interactions can be bidirectional • different study designs needed for unidirectional and bidirectional studies

31. Probes and ‘cocktails’ Probe • drug with a well characterised metabolic pathway • used to predict effects of test drug on other drugs = ‘prototype victim’ Cocktail • simultaneous administration of several probes • each is a marker for a different metabolic pathway • must be safe when given together • might given during a conventional repeat-dose study

32. Probes

33. Study design - population • often done in healthy volunteers, except when drug • toxic • anticancers • some antivirals • not tolerated by volunteers in full therapeutic dose (eg antipsychotics) so study best done in patients

34. Study design – dosing regimen 1 • single dose or repeated dose? • single dose useful to rule out interaction or illustrate principle • even in ‘single dose’ design, several doses of short half-life interactor may need to given to cover AUC of potential ‘victim’

35. Covering AUC • single dose design of drugs with disparate half-lives can miss an interaction due to inadequate coverage of AUC Potential victim Potential interactor

36. Covering AUC • solution is to give multiple doses of short half-life interactor Potential victim Potential interactor

37. Study design – dosing regimen 2 • repeated doses may be needed to yield high enough plasma levels • repeated dose useful to estimate extent of interaction in clinical situation • may be ethical or safety problems with very long dosing of volunteers • enzyme induction: requires 10+ days’ exposure to inducer

38. Specific studies - single dose - 1 Unidirectional PK study • effect of I on PK of V • inhibition: 2-way crossover • induction: 1 sequence • open Bidirectional PK study • effect of I on PK of V • effect of V on PK of I • up to 6 way crossover • usually 1 or 2 way • open

39. Specific studies - single dose - 2 • bidirectional PK and PD study • eg alcohol interaction • NB placebo

40. Specific studies - repeated dose • designs as single dose, but dose to steady state • can use ‘add-on’ design • advantage: mimics clinical use • disadvantage: inbuilt period effect • can study effect of inducers VVVVVVVVVVVVVVVVVVVVVVVVVV IIIIIIIIIIIIIIIIIIIIIIIIIIIIII PPPPPPPPPPPPP Continuous dosing of V Add-on continuous dosing of I Can be placebo controlled PK/ PD of V PK/PD of V

41. Decision analysis for interaction studies

42. Conclusions - drug interactions To obtain a data sheet with as few contraindications as possible and minimal likelihood of harming patients • understand the physical properties, & mechanisms of absorption, metabolism/elimination and pharmacodynamics of drug asap in development • use probes and cocktails early in development • to identify problems • to allow more coadministered drugs in Phase 2 & 3 • do specific study if interaction likely or if consequences clinically important or if you want no DDI text in the label • use a screening approach to rule out interactions with commonly co-prescribed drugs • don’t exclude a combination during clinical trials then expect regulators to allow coadministration