Application of PBPK to Drug Development in Rare Diseases - SMi ADEMT Conferece 2016

Takeda Development Centre Europe

Application of PBPK to Drug Development in Rare Diseases A Literature Review and Novel Application

11th Annual Conference and Exhibition on ADMET Monday 13th June 2016

Pau Aceves, MPharm, MSc. Senior Clinical Pharmacologist Quantitative Clinical Pharmacology Takeda Development Center Europe

Note: Any views expressed here are entirely my own and not of my employer or any pharmaceutical industry association


Introduction Rare Diseases – Increasing Trend in Drug Development

• End of ‘blockbuster’ model. • Incentives from FDA, EMEA • High unmet medical need • Phase II to launch timelines of

orphan drugs is 3.9 years vs. 5.42 years for non-orphan

• Higher probability of regulatory success 93% vs. 88% for non-orphan (p<0.05) [Phillips, 2012]

• Increasing strategic choice to develop drugs for rare diseases

• Opportunity to re-purpose products to orphan indication

Jarvis LM. Orphans Find a Home. C&EN, 2013 / http://www.tandfonline.com/doi/pdf/10.1517/21678707.2013.752128

http://www.tandfonline.com/doi/pdf/10.1517/21678707.2013.752128�


Introduction Application of PBPK

Zhao P et al. Clin Pharmacol Ther. 2011 Feb;89(2):259-67 (2011)

PBPK class of models characterize ADME processes and their underlying biological and physiological drivers.


Systems Approaches

Systems Pharmacology

PBPK

Introduction Rare Diseases – Challenges & Modelling Opportunities

• Many rare diseases are serious and life-threatening (frail patients)

• Lack of regulatory precedence • No established endpoints • Ethical challenges • Logistical trial challenges • Small number of patients • Heterogeneity in disease • Many diseases primarily affect

pediatric patients • Co-morbidities ie. hepatic/renal

impairment • Polypharmacy, paninhibitors etc.


Application of PBPK to Drug Development in Rare Diseases

Part 1: A Literature Review [from publically available data sources]


Case Study 1 [Public FDA Data, 2013] Ibrutinib (Janssen) for Mantle Cell Lymphoma (MCL)

• MCL accounts for about 6% of all non-Hodgkin lymphoma cases in the US

http://www.accessdata.fda.gov/drugsatfda_docs/nda/2013/205552Orig1s000ClinPharmR.pdf

http://www.accessdata.fda.gov/drugsatfda_docs/nda/2013/205552Orig1s000ClinPharmR.pdf�


Case Study 2 [Public FDA Data, 2014] Eliglustat (Cerdelga, Genzyme) for Gaucher disease

• Lysosomal storage disorder caused by a hereditary deficiency in the enzyme glucocerebrosidase, which affects 6,000 people in the U.S.

• PBPK used to quantify the impact of CYP2D6 polymorphisms and DDIs • Predicted 12 DDI scenarios involving CYP2D6 EM, IM, and PM • Predicted UMs would not achieve adequate conc. for therapeutic effect

• FDA approved eliglustat for treatment of EMs, IMs, or PMs of CYP2D6.

http://www.accessdata.fda.gov/drugsatfda_docs/nda/2014/205494Orig1s000ClinPharmR.pdf

http://www.accessdata.fda.gov/drugsatfda_docs/nda/2014/205494Orig1s000ClinPharmR.pdf�


• Inhibitor of DOT1L HMT with orphan status for MLL-r.

• MLL-r is an aggressive subtype of AML and acute ALL

• PBPK model predicted PK profiles of pinometostat after i.v. Infusion in adults

• Adult model transformed to pediatric setting based on ontogeny changes

• PBPK supported clinical trial design in rare populations and provided dosing recommendations for the ongoing pediatric trial

https://ash.confex.com/ash/2014/webprogram/Paper72544.html

Case Study 3 [Waters et al., 2013] Pinometostat (Epizyme) for Mantle Cell Lymphoma (MCL)

Adults

Children

https://ash.confex.com/ash/2014/webprogram/Paper72544.html�


Literature Review Summary

Drug Name How did PBPK help in rare diseases?

Ibrutinib FDA accepted the use of PBPK predictions to fill in unknown clinical gaps to help better inform the product label.

Eliglustat Inform drug development and guide clinical practice in rare diseases by simulating combined intrinsic and extrinsic factors

Pinometostat Help study designs and dose selection in rare pediatric populations. Leverage adult data. First record of prospective use of PBPK for dose selection in an on going study

Others Exendin-(9-39): Example of PBPK/PD (systems pharmacology)

Sildenafil i.v.: Streamline the Clinical Pharmacology study requirements

Ruxolitinib : First example of DDI via more than one pathway (CYP), with EMEA acceptance and label recommendation

Macicentan, Ponatinib, rhPTH[1-84], etc.


Application of PBPK to Drug Development in Rare Diseases

Part 2: A Novel Application [Unpublished Takeda]


PBPK in Rare Diseases Novel Application Bronchiolitis Obliterans Syndrome (BOS)

• Majority of the patients are post-lung transplant (50-60%)

• Results in fibrotic disease of the lungs with fatal outcome

• Rapid onset and is diagnosed when significant decline in pulmonary function has occurred

• Median survival of 3-4 years post diagnosis (oncology-like)

• Lack of effective therapies (none ↓ disease progression)

• High unmet medical need • Takeda re-purposed compound from oncology pipeline

• 3 Ph 1 studies ongoing, over 200 oncology patients dosed • No HV data available. No renal/hepatic impairment studies done (no CLR

data), no relevant (to BOS) DDI studies conducted.

http://www.medscape.com/viewarticle/466350_7

http://www.medscape.com/viewarticle/466350_7�

Takeda Development Centre Europe 12

PBPK in Rare Diseases Novel Application BOS Phase 1b Multiple Raising Dose Study Design

0.2 mg

0.6 mg

1.2 mg 1.2 mg

2 mg

3 mg 3 mg

4 mg

5 mg

Maximum Tolerated Dose = 6 mg [oncology]

30X

Anticipated Therapeutic Range

Cohort 1 0.2 → 1.2 mg QD Cohort 2 1.2 → 3 mg QD Cohort 3 3 → 5 mg QD

• Three sequential cohorts • Escalation within and between cohorts • Very low recruitment 0.2 pt/site/month


Oncology Population Reference • “Low potential for DDIs in

Oncology population” • Younger, no liver/renal impairment,

less con meds, prohibited strong inhibitors/ inducers in protocols

13

PBPK in Rare Diseases Novel Application BOS DDI Challenges

Median % fm and fe in absence of inhibitor(s)

CYP1A2 Liver

CYP2B6 Liver

CYP2C8 Liver

CYP2C9 Liver

CYP2C19 Liver

CYP2D6 Liver

CYP3A4 Liver

BOS a New Paradigm • Patients are on at least one NTI as per SoC immunosupression • Likely to present with prophylactic antibiotics/antifungals i.e. fluconazole • Patients with co-morbidities i.e. renal and hepatic impairment


PBPK in Rare Diseases Novel Application Is There Case for PBPK Modelling in BOS? • Scarce (hard to find) patient population • Narrow therapeutic index (but high unmet medical need) • Intrinsic factor challenges

– Patients are frail -> can’t do many assessments i.e. Intense PK/PD – Hepatic impairment – Renal impairment

• Extrinsic factor challenges – Taking NTIs – Taking paninhibitos (variable prescribed doses) – Taking multiple other co-medications

• Could PBPK simulations help manage risk so as to enable recruitment BOS patients without putting any individual subject at undue risk?


• A PBPK model developed in SimCYP • The final PBPK model consisted of:

– Full ADAM model – Full distribution model – rCYP data used to estimate the in

vivo contribution of CYPs – CLR was extrapolated using

allometry • Secondary model using the observed

human CL/F to derive CLint (retrograde) • Final model qualified by comparing the

simulated PK against the observed.

15

PBPK in Rare Diseases Novel Application PBPK Estimated DDI Potential – Model Overview


PBPK in Rare Diseases Novel Application Simulation – Ketoconazole DDI (1 pathway Inhibited)

• Simulation confirms low DDI potential with strong CYP3A4 inhibitor

0

5

10

15

20

25

30

35

40

45

144 146 148 150 152 154 156 158 160 162 164 166 168

Syst

emic

Con

cent

ratio

n (n

g/m

L)

Time - Substrate (h)

Mean Plasma Conc. vs. Time Profiles in HVs With and Without Ketoconazole

CSys Mean CSys Mean with Interaction

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

0 24 48 72 96 120 144 168

Syst

emic

Con

cent

ratio

n (n

g/m

L)

Time - Inhibitor (h)

Mean Plasma Ketoconazole Plasma concentration over Time Following 400 mg QD for 7 Days

ISys Mean 1

1.4 x AUC


0

1

2

3

4

5

6

7

8

9

0 24 48 72 96 120 144 168

Syst

emic

Con

cent

ratio

n (m

g/L)

Time (h)

Mean Plasma Fluconazole Plasma concentration over Time Following 200 mg QD for 7 Days

ISys 1

0

5

10

15

20

25

30

35

40

45

50

144 168

Syst

emic

Con

cent

ratio

n (m

g/L)

Time (h)

Mean Plasma Conc. vs. Time Profiles in HVs With and Without Fluconazole

CSys Csys with interaction

PBPK in Rare Diseases Novel Application Simulation – Fluconazole DDI (≥2 pathways Inhibited)

• Moderate DDI (i.e. ≥ 2 & < 5-fold AUC) when ≥2 pathways are perturbed

2.3 x AUC


0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

144 150 156 162 168

Syst

emic

Con

cent

ratio

n (m

g/L)


CSys - Pop 1 CSys - Pop 2

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

144 150 156 162 168

Syst

emic

Con

cent

ratio

n (m

g/L)


CSys - Pop 1 CSys - Pop 2 CSys + Interaction - Pop 2

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

144 150 156 162 168

Syst

emic

Con

cent

ratio

n (m

g/L)


CSys - HVs CSys - Pop 3

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

144 150 156 162 168

Syst

emic

Con

cent

ratio

n (m

g/L)


CSys - HVs CSys - Pop 3 CSys + Interaction - Pop 3

Mean Plasma Conc. vs. Time Profiles in HVs (Pop 1) and in Subjects with Mild Liver Impairment (Pop 2)

With and Without Fluconazole

PBPK in Rare Diseases Novel Application PBPK Simulations – 1 Intrinsic Factor ± Fluconazole DDI

• Moderate increase in exposure (i.e. ≥ 2 & < 5-fold AUC) in mild renal or hepatically (CPA) impaired subjects with or without Fluconazole.

2 x AUC

3.4 x AUC 2 x

AUC

3.4 x AUC

Mean Plasma Conc. vs. Time Profiles in HVs (Pop 1) and in Subjects with Mild Renal Impairment (Pop 3)

With and Without Fluconazole


PBPK in Rare Diseases Novel Application Worst Case Simulation – Justification for MRD Starting Dose

• Starting dose Cohort 1 = 0.2 mg • Max dose Cohort 1 = 1.2 • Oncology MTD = 6 mg • Worst-case scenario simulation

with multi-factors → 4-fold • HED at NOAEL = 1 mg • Starting dose acceptable

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

144 150 156 162 168

Syst

emic

Con

cent

ratio

n (m

g/L)


Mean Plasma Conc. vs. Time Profiles in HVs (Pop 1) and in Subjects with Mild Liver Impairment With

Fluconazole and Diltiazem

CSys with interaction CSys - Pop 1

3.7 x AUC

0.2 mg

0.6 mg

1.2 mg

Cohort 1


• Study Protocol and PBPK simulated DDI table presented to FDA as part of preIND Meeting Briefing Document

• Weak DDI when a single metabolic pathway is strongly inhibited • Moderate when ≥2 pathways are perturbed; or in mild hepatics

20

PBPK in Rare Diseases Novel Application PBPK Estimated DDI Potential – Trial Simulations


Risk Assessment

• Strategy to assess risk for each individual • Ensures safeguards, while enabling recruitment in BOS • Requires additional ‘third-party’ unblinded PK analyist

PBPK Simulation (if needed)

Blinded CP reviews Con Meds & Liver

Function

Not expected

Close to MTD

Safety Alone

Level of Monitoring

Could AUC or Cmax be >

MTD at the 3rd dose?

Safety & PK

Exceeds Exclude!

PK Analysis

Interim blinded PK analysis by

team CP

Expedited PK analysed by

unblinded CP

Learn from preliminary results

Obs. PK > MTD withdraw

Stopping Rules

Obs. PK = MTD don’t escalate

Pred. next dose PK > MTD don’t

escalate

21 CP: Clinical Pharmacologist; Obs.: Observed; Pred.: Predicted; MTD: Maximum Tolerated dose

PBPK in Rare Diseases Novel Application PBPK DDI Risk Minimization Strategy for MRD Study

BOS


How did PBPK help in BOS?

• Quantified the previously unknown DDI risk for BOS subjects • Simulations helped communicate the risk of DDI in BOS • Helped simulate “impossible trials” / “what if” scenarios • Influenced the study exclusion criteria • Appropriateness of the starting dose for First-in-BOS MRD • Supported the DDI strategy during FDA preIND meeting • Confirmed the low impact of CYP2C19 PM in Japanese • May have helped prevent exceeding MTD exposures [as the

project and MRD study did not go ahead] • PBPK was an enabling tool to safely allow the

investigation of a drug in a complex rare disease like BOS


Acknowledgements

• Dr. Graham Scott, Senior Director at Takeda, London. • Dr. Paul Goldsmith , Scientific Director at Takeda, London. • Dr. Lachy McLean, Vice President, Experimental Medicine

Head Immunology at Takeda, California. • Dr. Chirag Patel, Scientific Director, Clinical Pharmacology at

Takeda, Boston. • Dr. Beverly Knight, Clinical Pharmacology Lead at Pfizer,

California. • Dr. Ruth Lock, Consultant in DMPK and Clinical

Pharmacology, London. • Nuria Bech MBA, Clinical Trials Study Leader at Hoffmann-

La Roche, UK.


Thank You

Health & Medicine

Application of PBPK to Drug Development in Rare Diseases - SMi ADEMT Conferece 2016