Statistical Considerations in Biosimilar Clinical Development

Jean Pan, Eric M. Chi

2015 Duke-Industry Statistics Symposium, 23 October 2015

Outline

Background

o Definitions of Biosimilars

o Elements of Biosimilar Development

o Regulatory Requirements for a Biosimilar MAA/BLA

o Clinical Requirements for Biosimilar Development

Statistical Considerations for Biosimilar Clinical Studies

o Endpoints

o Equivalence Margins

o Type I Error Rate

o Totality of Evidence

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BACKGROUND

What are Biosimilars?

• The biological product is highly similar to the reference product notwithstanding minor differences in clinically inactive components; and

• There are no clinically meaningful differences between the biological product and the reference product in terms of the safety, purity, and potency of the product

• The biological product is highly similar to the reference product notwithstanding minor differences in clinically inactive components; and

• There are no clinically meaningful differences between the biological product and the reference product in terms of the safety, purity, and potency of the product

EMA Definition

• A biosimilar is a biological medicinal product that contains a

version of the active substance of an already authorised original

biological medicinal product (reference medicinal product).

• A biosimilar demonstrates similarity to the reference medicinal

product in terms of quality characteristics, biological activity, safety

and efficacy based on a comprehensive comparability exercise

• A biosimilar is a biological medicinal product that contains a

version of the active substance of an already authorised original

biological medicinal product (reference medicinal product).

• A biosimilar demonstrates similarity to the reference medicinal

product in terms of quality characteristics, biological activity, safety

and efficacy based on a comprehensive comparability exercise

FDA Definition

U.S. Food and Drug Administration. Guidance for industry: Quality considerations in demonstrating biosimilarity to a reference protein product. 2015.

http://www.fda.gov/downloads/drugs/guidancecomplianceregulatoryinformation/guidances/ucm291134.pdf

European Medicines Agency. Guideline on Similar Biological Medicinal Products. 2014

[http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2014/10/WC500176768.pdf

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Elements of Biosimilars Development

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1. Structure 1. Structure

2. Function 2. Function

3. Animal Toxicity/Efficacy 3. Animal Toxicity/Efficacy

4. Human PK/PD 4. Human PK/PD

5. Clinical Safety 5. Clinical Safety

6. Clinical Effectiveness 6. Clinical Effectiveness

7. Immunogenicity 7. Immunogenicity

8. REMS & Pharmacovigilance 8. REMS & Pharmacovigilance

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Requirements for Biosimilar MAA/BLA

CMC Preclinical Clinical

Drug substance – Manufacture – Characterisation – Control – Reference

standard – Container – Stability

Drug product – Description – Development – Manufacture – Control – Reference

standard – Container – Stability

+ Comparability data + Analytical

comparison with reference product

Pharmacology – Primary pharm.

– Secondary pharm.

– Safety pharm.

– Interactions Pharmacokinetics

– ADME

– Interactions Toxicology

– Single dose

– Repeat dose

– Genotoxicity

– Carcinogenicity

– Reproduction

– Local tolerance

Pharmacology Pharmacokinetics

– Single dose

– Repeat dose

– Special populations

Efficacy and safety – Dose finding

– Schedule finding

– Pivotal • Indication 1

• Indication 2

• Indication 3

• Indication 4

Post-marketing studies – Safety in larger

population

– Efficacy in other indications

– Immunogenicity

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Clinical Requirements for Biosimilar Development

One single dose clinical pharmacokinetic (PK) study to establish bioequivalence (BE) to Reference (US) and Reference (EU), and support bridging between Reference (US) and Reference (EU).

o Healthy volunteers

o BE: 80% - 125% margin for the ratio of geometric mean in AUC and Cmax

One clinical efficacy/safety/immunogenicity study to establish clinical equivalence to a Reference

o “Sensitive” population/endpoints

o Similarity in efficacy

o Non-inferiority in immunogenicity and safety

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STATISTICAL CONSIDERATIONS FOR BIOSIMILAR CLINICAL STUDIES

Endpoints

Selection of endpoints depends on the type of biosimilar study being conducted.

o PK endpoints: 𝐴𝑈𝐶0−∞, 𝐶𝑚𝑎𝑥, 𝐴𝑈𝐶0−𝑡

o PD endpoints: Product-dependent, where available

o Efficacy endpoints

• Oncology: objective response rate, progression-free survival

• RA: ACR20*, DAS28-CRP**

• Psoriasis: PASI % Improvement***

* ACR20: 20% improvement in American College of Rheumatology (ACR) core set measurements from baseline

** DAS28-CRP: Disease activity score (28 joints) - serum C-reactive protein

*** PASI: Psoriasis Area and Severity Index

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Endpoints (cont’d)

Points to consider in selecting efficacy endpoints

o Objective of biosimilar clinical efficacy study is to show biosimilarity, not efficacy.

o The primary endpoint(s) can be different from those in the reference product’s clinical trials if scientifically justified.

o Endpoints should be clinically relevant and sensitive in detecting clinically meaningful differences in safety and effectiveness.

o The primary endpoint must be one for which there is a good basis for knowing the effect of the active control, one that would permit a smaller study or was more feasible given current event rates.

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Endpoints (cont’d)

Metrics for treatment effect of a binary endpoint between the test and reference groups (𝑃𝑇 and 𝑃𝑐 ) o Risk difference: RD = 𝑃𝑇 𝑃𝑐

o Relative risk (or risk ratio): RR = 𝑃𝑇 / 𝑃𝑐

o Odds ratio: 𝑂𝑅 =𝑃𝑇

1−𝑃𝑇

𝑃𝑐

1−𝑃𝑐

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Endpoints (cont’d)

Choice of metrics

o Statistical properties

• RD is affected more by variability in the event rates than RR or OR.

• RR is most powerful, but is study outcome dependent (ie, a lower than expected event rate observed from the biosimilar trial will equate to a study-dependent narrower margin on RD)

o Interpretation

• RD is most straight-forward to interpret.

o Regulatory agency’s experiences

• FDA: RR (Onc) and RD (Rheum)

• EMA and PMDA: RD

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Endpoints (cont’d)

Comparison of RR vs. RD

o Assume 𝑃𝑐= 50%

• RR margin=(0.75, 1/0.75) planned RD margin=(-12.5%,16.7%)

o If 𝑃𝑐= 40% is observed,

• RR margin=(0.75, 1/0.75) actual RD margin=(-10%,13.3%)

o Study power

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Equivalence Margins

Margins should be pre-specified and justified on both statistical and clinical grounds.

o Any widening beyond (0.8,1.25) for PK parameters requires sufficient justification.

o The margins for efficacy endpoints are derived and justified on a case-by-case basis, taking into consideration the characteristics of disease, property of endpoint, and available information on the reference product.

Equivalence (EQ) or Non-inferior (NI) test to establish no clinically meaningful differences?

o Typically, an equivalence design with symmetric inferiority and superiority margins would be used. The margins can be different for some cases.

o For some cases, one-sided NI design may be appropriate.

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Equivalence Margins (cont.)

The NI margin for efficacy endpoints is derived following the FDA NI guidance.

o Meta analysis of effect (against placebo) from historical data of the reference (M1)

• Biosimilar is better than placebo

o To preserve a fraction of the effect of the reference (M2< M1)

• Biosimilar is better than placebo and is closer to the reference (e.g., M2 50% M1)

o Clinical judgment

• Minimum clinically meaningful difference

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Type 1 Error

Let Δ be the true (unknown) difference between the test and reference groups

EQ hypothesis:

H0: Δ ≤ Δ𝐿 or Δ ≥ Δ𝑈 vs. HA: ΔL < Δ < Δ𝑈

where Δ𝐿(≤ 0) and Δ𝑈 (≥ 0) are pre-specified margins.

The above test at level α is tested using two one-sided tests (TOST), each at level α*:

H0L: Δ ≤ Δ𝐿 vs. HAL: Δ > Δ𝐿

and

H0U: Δ ≥ Δ𝑈 vs. HAU: Δ < Δ𝑈

* Berger and Hsu, Statistical Science, 1996, Vol. 11, No. 4, 283-319

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Type 1 Error (cont.)

A level TOST is operationally identical to comparing the 2-sided 100(1-2)% confidence interval (CI) with the equivalence margin*.

To preserve a study-wise type I error rate at level,

o 2-sided 90% CI for 5.0% Type-1 error

o 2-sided 95% CI for 2.5% Type-1 error

Regulatory agency’s experiences

o PK endpoints: 5.0% Type-1 error

o Efficacy endpoints:

• FDA: 5.0% Type-1 error

• EMA and PMDA: 2.5% Type-1 error

* Westlake WJ. Response to T.B.L. Kirkwood: bioequivalence testing - a need to rethink. Biometrics. 1981;37:589-594;

Schuirmann DJ. On hypothesis testing to determine if the mean of a normal distribution is contained in a known interval. Biometrics. 1981;37:617.

Berger RL, Hsu JC. Bioequivalence trials, intersection-union tests and equivalence confidence sets. Statistical Science. 1996;11:283-319.

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Totality of Evidence – FDA

o FDA will evaluate the integration of various

types of information to provide an overall

assessment that a biological product is (or is

not) biosimilar to an approved reference

product.

o Approval of a proposed biosimilar product is

based on the totality of the evidence

submitted by the biosimilar sponsor.

Analytical

Nonclinical

Clin Pharm

Additional

Clinical

Studies

U.S. Food and Drug Administration. Guidance for Industry: Scientific Considerations in Demonstrating Biosimilarity to a Reference Product. 2015.

http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM291128.pdf

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Totality of Evidence – Implementation

Planning

o Design of the Pivotal Clinical Efficacy/Safety Study

• Efficacy margins

• Type-1 errors

Reviewing

o Summary of Totality of Evidence

• Analytical, PK, Clinical?

• Combining evidences?

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Totality of Evidence – Objective (Statistical) Assessment

Planning

o What are the requirements for the pivotal clinical study based on the outcome of the analytical and PK results?

Reviewing

o Can the evidences from analytical, PK, and clinical be quantitatively synthesized?

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Thank You for Your Attention!

Jean Pan, Eric M. Chi

2015 Duke-Industry Statistics Symposium, 23 October 2015