Comparability Challenges for ATMP Development and Supply to the Patients

EBE, London 2017

Christina Basford

Introduction Comparability Challenges

•  ATMPs at GSK

•  Original Strategy

•  Current / Future Strategy and Associated Challenges

•  Summary

ATMPs at GSK

Summary of CGT technologies – GSK View

Vector

Deliveryvehicle(e.g.len2virus,AAV)

DonorCell

Exvivo,autologousCGTproduct

Exvivo,allogeneicCGTproduct

InvivoGTproduct

Transduc2on

Transduc2on

CellTransfec2on

•  ATMPs broader than Gene Therapy. •  GSK focus has been on Gene Therapy hence the focus of this talk

Summary of CGT technologies – GSK View

ExvivoGeneTherapyforAdenosine

Deaminase-SevereCombinedImmuno-Deficiency(ADA-SCID)• Fatal• Life-threateningopportunis3cinfec3ons

• Prevalence:1in200,000

Commercial Product

Promise and Challenge of CGT Medicines Pipeline

ADA-SCID MLD & WAS Oncology

10

100

1000

10,000

100,000

Patient numbers

Original Strategy: Defining Process Changes and Evaluating Comparability

Why do we need to do anything? •  Low volume, acute need - why not just go with it?

•  Data shows wide variability, lack of process robustness −  e.g. Vector Copy Number

•  Raw materials, impurities, containment improvements needed

We have to do something - but not everything... •  Changes introduced with the aim to:

- Increase scale of manufacture (vector) - Increase process efficiency/performance consistency and robustness - Decrease variability throughout the process - Increase sterility assurance

•  ...but no radical redesigning or over-complicating the process

Process changes for production

Defining the control strategy

CQAs What product attributes impact safety / efficacy?

CPPs Which parameters impact CQAs?

Testing Strategy

Based on the controls in place, is testing required for the CQA?

RMs Which raw materials impact CQAs?

Assessments during Process Development

Quality Target Product Profile

CQA – Critical quality attribute CPP – critical process parameter

Defining the Control Strategy CQAs as the Foundation of the Control Strategy

A physical, chemical, biological or microbiological property or characteristic that should be within an appropriate limit, range, or distribution to ensure the desired product quality

CQAs are: -Product attributes with potential

to impact safety or efficacy

- Baseline for all stages of product lifecycle

CQAs are NOT: - Analytical methods

-Specifications

Process Changes and Comparability Comparability Study Design

2 full scale vector campaigns 3 full scale vector batches

2 Vector campaigns (Study 1)

Transduction 3 lots of pooled BM CD34+ cells

In Vitro comparability Stability

VS

Clinical Process Commercial Process

Study 1 Vector

Study 2 Cells

In Vitro comparability Stability In Vitro

comparability Stability

3 Vector batches (Study 1)

Transduction 3 lots of pooled BM CD34+ cells

In Vitro comparability Stability

Process Changes and Comparability Interpretation of Results

•  Clinical and commercial process batches comparable

•  Colony forming unit (CFU) values higher than historical range

–  difference attributed to starting material (healthy donor vs patient bone marrow)

•  Values within range obtained from process development experiments (healthy donor)

•  Comparable change in clonogenic potential (DS/CD34+) between clinical and commercial batches

•  ∆CFU within historical range - comparability batches and process development data

Current / Future Strategy & Associated Challenges

Current Regional Cell Processing Hubs

Bespoke, manual process Fully automated system

with integrated QC testing

‘Ballroom’ Suites in Regional Hubs with

Exact Copy Automation

Multiple Automated units in a ballroom suite in regional hubs

Cell Process Scale out – Future Direction

Challenges Technical GMP/Regulatory

Fully closed, automated process QA, QP Release Local? In-line, in –process analytics Manufacturing within hospital

Continuous process validation Robust tracking Raw Material sourcing/supply Troubleshooting, deviation management

Process and product drift over time 10

Decentralised Cell Processing

•  Improved methods to measure input and output material •  Gain targets to make process improvements •  Next generation techniques for measuring comparability include:

A: Transcriptomics B: Proteomics

•  Data generated so far has been preliminary and has mainly served as a proof of concept

•  Next steps: Apply these learnings to our oncology assets

Next Generation Comparability Mapping cells to improve cell process & inform comparability

We are looking for markers that are subject to process changes but robust enough not to be affected by donor variability.

Comparability Challenges Where are the road blocks?

•  New paradigm for medicine •  Assets often developed in an academic environment •  Treatments mainly autologous •  Availability of good in vivo models •  Healthy donor material is used for comparability •  Supply of raw materials •  Characterisation/Potency testing •  Consider manufacturing site changes (e.g. sites in Europe and US)? •  Implications for a true decentralized solution? •  Considerations for transfer of analytical methods

Summary

Summary

•  ATMPs have the potential to be transformative medicines

•  Current manufacturing paradigms will need substantial innovation in all aspects – Technical, Regulatory & Quality - to supply global demand

- A defined control strategy is vital - Comparability can be complex but is there to help us - The control strategy can act as the basis for technology transfer

•  Close collaboration between all stakeholders is needed to bring these transformational medicines to a wider patient population

Acknowledgments

Our Partners at TIGET, Molmed & Adaptimmune

GSK CGT including:

•  Joe Tarnowski

•  Amol Ketkar

•  Steve Howe

•  Aileen Kirkpatrick

• Michele Myers

•  Conrad Vink

•  Tony Lamus

•  Sadia L’Baouch

•  Rob Piperno

•  Alexis Cockroft