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Drug-drug interactions that really matter – focus on transporters AGAH Annual Meeting 2014 │13 Mar 2014 Jens Rengelshausen


Content

Which drug-drug interactions do really matter? 3

Clinically relevant transporter-mediated drug-drug interactions 5

DDI - Transporter 13 Mar 2014

Predicting transporter-mediated drug-drug interactions 16


Pharmacokinetic drug-drug interactions: basic principles


Drug-drug interaction (DDI): One drug (perpetrator) alters the intensity of pharmacological effects of another drug (victim) when administered concomitantly.

10 20 30 9 8 7 Victim drug concentration

20

40

60

80

100

% o

f ind

ivid

uals

resp

ondi

ng

Therapeutic Effects

Adverse Effects

Exposure-response relation determines clinical relevance of

pharmacokinetic drug-drug interaction


Clinical relevance: high-priority drug-drug interactions


Electronic knowledge base utilized to generate clinical decision support (PHS MKB) – Selection of high-priority DDIs out of 3327 DDI pairs by expert panel based on severity of

clinical outcome, monitoring options, probability of occurrence, evidence from literature – 15 DDIs identified: 7 pharmacodynamic interactions, 8 pharmacokinetic interactions

Selected highly clinically significant pharmacokinetic drug-drug interactions

Victim drug Perpetrator drug PK and clinical consequence Triptans MAO-A inhibitors AUC▲ up to 7-fold, cardiovascular ADRs Ramelteon Strong CYP1A2 inhibitors AUC▲ up to 190-fold, CNS ADRs Tizanidine CYP1A2 inhibitors AUC▲ up to 10-fold, hypotonia Lova-/Simvastatin CYP3A4 inhibitors AUC▲ up to 20-fold, rhabdomyolysis Irinotecan CYP3A4 inhibitors SN-38 AUC▲ 2-fold, cytotoxicity Ergot alkaloids CYP3A4 inhibitors Vasoconstriction, necrosis (ergotism) Protease inhibitors Strong CYP3A4 inducers AUC▼ by 80%, lack of efficacy Atazanavir Proton pump inhibitors AUC▼ by 60%, lack of efficacy

Phansalkar S et al. J Am Med Inform Assoc 2012;19:735-43


Drug transport proteins: gatekeepers of the body


≈ 30 drug transporters

ABC transporters

SLC transporters

Absorption Disposition Uptake for metabolism

and excretion Excretion

> 400 membrane transport proteins in human genome

Zhang L et al. Clin Pharmacol Ther 2011;89:481-4

Drug-drug interaction potential !


Alignment on relevant transporters for drug ADME


International Transporter Consortium

(ITC)

Goal 1 To provide overview of key drug transporters involved in drug ADME

Goal 3 To provide criteria for the design and conduct of clinical studies of transporter-related DDIs => decision trees

Goal 2 To provide examples of various technologies in studies of transporter-related DDIs

Huang SM and Woodcock J. Nat Rev Drug Discov 2010;9:175-6

Key mile- stones

FDA critical path initiative: ITC established in 2007 First Workshop 2008, first White Paper 2010 ITC recommendations taken up in revised draft of FDA Guidance for

Industry on Drug Interaction Studies in February 2012 Second Workshop March 2012, second set of White Papers 2013

Giacomini KM et al. Nat Rev Drug Discov 2010;9:215-36

11 international experts from

academia

11 international experts from

pharma-industry

2 experts from FDA


Drug transporters of clinical importance selected by the ITC


ABC transporters involved in drug absorption, disposition and excretion Transporter Relevant tissue Substrate (e.g.) Inhibitor (e.g.) P-glycoprotein Intestinal enterocyte Digoxin Quinidine (P-gp, MDR1) Kidney proximal tubule Clarithromycin Hepatocyte (canalicular) Brain endothelia BCRP as P-glycoprotein Topotecan Elacridar SLC transporters involved in drug disposition and excretion Transporter Relevant tissue Substrate (e.g.) Inhibitor (e.g.) OATP1B1 Hepatocyte (sinusoidal) Pravastatin Cyclosporine OATP1B3 Hepatocyte (sinusoidal) Rosuvastatin Lopinavir/ritonavir OAT1 Kidney proximal tubule Cidofovir Probenecid OAT3 Kidney proximal tubule Furosemide Probenecid OCT2 Kidney proximal tubule Metformin Cimetidine MATE1, MATE2K Kidney proximal tubule Metformin Cimetidine Hepatocyte (MATE1)

Zhang L et al. Clin Pharmacol Ther 2011;89:481-4 Hillgren KM et al. Clin Pharmacol Ther 2013;94:52-63


Drug transporters in the intestinal epithelia


Intestinal lumen (apical)

Blood (basolateral)

ATP P-gp

BCRP ATP

MRP2

MCT1

ASBT

PEPT1 PEPT2

OATP1A2 OATP2B1

ATP

ATP

OCT1

OSTα OSTβ

MRP3

ENT1 ENT2

Hillgren KM et al. Clin Pharmacol Ther 2013;94:52-63

Clinical relevance – P-gp and BCRP limit

oral bioavailability of drug substrates

– Inhibition of P-gp or BCRP => increased substrate bioavailability

– High gut concentrations of inhibitors lead to max. transport inhibition

König J et al. Pharmacol Rev 2013;65:944-66

GRÜNENTHAL Name der Präsentation Datum GRÜNENTHAL DDI - Transporter 13 Mar 2014

Digoxin-clarithromycin interaction trial – Cross-over trial in 12 healthy subjects – Digoxin 0.75 mg SD p.o., in n=3 also i.v. – Clarithromycin 250 mg BID for 3 days

PK interaction results – Digoxin AUC after p.o. ▲ 1.7-fold – Renal tubular digoxin secretion ▼ by 40% – Digoxin AUC after i.v. ▲ only 1.2-fold

Intestinal absorption interaction via P-gp: digoxin-clarithromycin

0 2 4 6 8 10 12 24

0

1

2

3

4

5

6

Time (hours)

Plas

ma

Dig

oxin

(µg

l-1)

Placebo Clarithromycin05

101520253035

Dig

oxin

AU

C(0

,24)

(µg

l-1 h

)

P = 0.002

0 2 4 6 8 100

5

10

15

20

25

30

35

Time (hours)

Plas

ma

Dig

oxin

(µg

l-1)

A

Rengelshausen J et al. Br J Clin Pharmacol 2003;56:32-8

○ Placebo ● Clarithromycin


Inhibitor concentration effects – Highest interaction effect (digoxin ratios)

during absorption phase of clarithromycin – Est. plasma / gut conc.: 2.7 / 1337 µM – In vitro IC50 for interaction: 4.1 µM

Clinical consequences – Digoxin therapeutic range: 0.9 – 2 µg/l – Due to narrow therapeutic index of digoxin

AUC▲ >1.25-fold clinically important – Clinically relevant DDI

Intestinal P-gp inhibition by clarithromycin: digoxin toxicity risk

Rengelshausen J et al. Br J Clin Pharmacol 2003;56:32-8

0 2 4 6 8 10 12200

400

600

800

1000

1200

1400

Time (hours)

Plas

ma

Cla

rithr

omyc

in (µ

g l-1

)

200 400 600 800 1000 1200

11.21.41.61.8

22.2

Plasma Clarithromycin (µg l-1)P

lasm

a D

igox

in R

atio

10 min

12 h

Zhang L et al. Xenobiotica 2008;38:709-24


Drug transporters in brain capillary endothelial cells


Blood (apical)

Brain (basolateral)

ATP P-gp

BCRP ATP

MRP4

MRP5

ENT2

OATP1A2 OATP2B1

ATP

ENT1 ENT2


ATP Clinical relevance

– P-gp (and BCRP) constitute BBB for substrate drugs

– Transport inhibition => potential CNS ADRs

– Unbound concentrations of marketed inhibitors at BBB < in vitro IC50 of transport => low risk for relevant DDI

Kalvass JC et al. Clin Pharmacol Ther 2013;94:80-94


Drug transporters in the hepatocytes


Blood (sinusoidal)

ATP P-gp

BCRP ATP

MRP2 MATE1

OCT1

ATP

MRP3 MRP4 MRP6

NTCP

ENT2 ENT2


ENT1

BSEP

OATP1B1

OAT2 OAT7

Bile (canalicular)

ATP

ATP

OATP1B3

OATP2B1

OSTα OSTβ

Clinical relevance – Liver uptake transport

basis for subsequent drug metabolism

– Inhibition of liver uptake => increased plasma exposure of substrate

– Drug inhibition of MRP or BSEP => DILI risk

– Canalicular MRP with sinusoidal salvage



Rosuvastatin-cyclosporine interaction – 10 patients after heart transplantation – Rosuvastatin 10 mg SD and MD – Stable cyclosporin treatment – Historic control with 21 healthy subjects – Rosuvastatin AUC▲ 7.1-fold after MD

Pharmacogenetic impact on statin PK – OATP1B1 c.521T>C and BCRP c.421C>A

both influence rosuvastatin AUC – OATP1B1 SNP: Simvastatin AUC▲ 3.2-

fold in CC vs. TT; Odds ratio for myopathy after 80 mg simvastatin 16.9 in CC vs. TT

– Clinically relevant DDI between rosuvastatin and cyclosporine

Hepatic excretion interaction via OATP1B1 and BCRP

Healthy controls Heart transplant recipients0

100

200

300

400

Rosuvasatin AUC(0-24) (ng*h/mL)

OATP1B1 BCRP1

1.2

1.4

1.6

1.8

2

2.2

2.4

2.6

Fold increase in rosuvastatin AUC

c.521CC/TT c.421AA/CC

Simonson SG et al. Clin Pharmacol Ther 2004;76:167-77 Niemi M. Clin Pharmacol Ther 2010;87:130-33


Drug transporters in the renal proximal tubules


Tubule lumen (apical)

Blood (basolateral)

ATP P-gp

BCRP ATP

MRP2, MRP4

MATE1 MATE2K URAT1

PEPT1, PEPT2

OCTN1, OCTN2

ATP

OCT2

OATP4C1

ENT2


ENT1

OAT4

OAT1

OAT2

OAT3

Clinical relevance – Renal drug clearance =

glomerular filtration + tubular secretion – tubular re-absorption

– Drugs with high tubular secretion at risk for renal transport DDIs

– Uptake inhibition may prevent nephrotoxicity



Drug interactions influencing renal tubular drug secretion


DDIs via OCT2 and MATE1 and 2K DDIs via OAT1 and OAT3

Broad substrate overlap Probenecid potent inhibitor but extent of

drug-drug interactions is moderate: – Cephradine AUC▲ 3.6-fold – Acyclovir AUC▲ 1.4-fold – Furosemide AUC▲ 2.9-fold – Methotrexate Css▲ 2-fold

Beneficial use of probenecid interactions: – Increase of exposure and t1/2 of

benzylpenicillin – Protection against cidofovir nephrotoxicity

=> probenecid must be co-administered

Broad substrate overlap Cimetidine potent inhibitor (MATE > OCT)

but extent of interactions is moderate: – Metformin AUC▲ 1.4-fold – Dofetilide AUC▲ 1.5-fold – Procainamide AUC▲ 1.4-fold – Pindolol AUC▲ 1.5-fold

Interactions previously attributed to OCT2 may predominantly be mediated by MATEs due to higher inhibitor affinity

Zhang L et al. Clin Pharmacol Ther 2011;89:481-4 Hillgren KM et al. Clin Pharmacol Ther 2013;94:52-63


Transporter Studies in Drug Development: ITC + FDA view


Evaluation of an investigational drug as substrate for drug transporters – Decision tree from FDA Guidance (2012) modified by ITC after second workshop (2012)

All NMEs

Determine whether NME is P-gp and/or BCRP

substrate in vitro

Hepatic or biliary secretion major? e.g. ≥ 25% of total clearance or unknown?

Renal active secretion major? e.g. ≥ 25% of total clearance or unknown?

Determine whether NME is OATP1B1 and/or OATP1B3

substrate in vitro

Determine whether NME is OAT1, OAT3, OCT2 and/or

MATE substrate in vitro

Refer to OATP1B1/1B3 decision tree for need to conduct in vivo studies

Refer to OAT1/3 and OCT2/MATE decision tree for potential in vivo studies

Refer to P-gp and BCRP decision tree for need to conduct in vivo studies

Giacomini KM and Huang SM. Clin Pharmacol Ther 2013;94:3-9

Yes Yes


PBPK modeling and drug-drug interactions – principles


Physiologically based pharmacokinetic (PBPK) modeling and simulation – Dynamic tool to predict PK of drugs and effects of intrinsic + extrinsic factors in humans

System component (drug-independent)

Physicochemical

Distribution

Elimination

Zhao P et al. Clin Pharmacol Ther 2011;89:259-67

Absorption and first pass metabolism

Drug-dependent component

Absorption

Distribution

In vitro human ADME and MOA data In vivo human PK data

Metabolism and transport

DDI

MOA

PK of metabolite(s)

PK-PD relationship

Lung

Rapidly perfused organs

Slowly perfused organs

Kidney

Liver

Intestines

Blood

Blood

Dosing Ellimination

PBPK model

Model refine-ment


PBPK modeling and drug-drug interactions – practice


Prediction of transporter-mediated DDIs Chances and limits of PBPK modeling

Help optimizing clinical trials: – dosing regimens – sampling schemes – need for additional trials

Prediction of complex DDIs involving transporters and metabolic enzymes

Quality of in vitro model information may limit utility of PBPK approaches

Integration of in vivo data to refine PBPK model: “predict, learn, confirm“ iterations

15 submissions to FDA containing PBPK analyses on DDIs (2008 – 2011)

Specialized PBPK database software available, e.g. Simcyp Simulator

PBPK models to incorporate permeability-limited tissue compartments for intestine, liver and kidney with active transport

Detailed kinetic characterization needed Transporter interaction related changes in

tissue concentrations may be predicted Examples of successful prediction of

transporter-mediated DDIs still limited: – Cyclosporine – repaglinide (OATP1B1) – Gemfibrozil – pravastatin (OATP1B1) – Verapamil – digoxin (P-glycoprotein)

Zamek-Gliszczynski MJ et al. Clin Pharmacol Ther 2013;94:64-79 Zhao P et al. Clin Pharmacol Ther 2011;89:259-67


Transporter-mediated drug-drug interactions: summary


Relevance

Transporter-mediated DDIs may have high clinical relevance, but their extent is rather lower than of DDIs mediated by metabolic enzymes.

Transporter-mediated intestinal absorption, hepatic uptake and renal tubular secretion are main sites of transporter-mediated DDIs.

Clinical relevance of transporter-mediated DDIs at BBB is still unclear. Emerging data on newly characterized transporters may change

mechanistic understanding of clinically relevant DDIs.

Actions

Transporter-medicated DDIs are to be considered in drug development. NMEs are recommended to be investigated as potential substrates and/or

inhibitors of relevant drug transporters according to decision trees. Results need to be reflected in drug labels in order to prevent adverse drug

reaction or lack of efficacy caused by transporter-mediated DDIs. Well refined PBPK modeling may enable optimal predictions of transporter-

mediated DDIs and help optimizing or even omitting clinical trials.

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