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Cell Therapy… how to move from Heroic Medicine to Clinical Reality

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Presentation on theme: "Cell Therapy… how to move from Heroic Medicine to Clinical Reality"— Presentation transcript:

1 Cell Therapy… how to move from Heroic Medicine to Clinical Reality
Mark Briggs, PhD Cell Therapy Technologies GE Healthcare Life Sciences

2 An increasing percentage of healthcare dollars will be spent on new medicines
Key Trends Increasing personalization of medicine Spending on specialty medicines to reach $ billion in 2017, with total aggregate spending on medicines to exceed $1.2 Trillion (IMS Health) Cancer cellular immunotherapy expected to reach $20 Billion by 2020 Patients treated by therapy type 2005 ($650B)* 2025 ($1,650B) What market looked like 9 years ago and the relative distribution of patients treated by therapy type In 2014, small and large molecule therapies still dominate…. In 2025, we can predict that the % patients treated with cell & gene therapies would increase, with approvals, and this number would translate into 1000’s, possible 100K’s of dose… The point here is that we (the industry) will need an infrastructure to support the manufacture of these therapies….a lot of work ahead of us.. In 2015, 2% translates into 1000 – 100,000’s of doses How big are we going to be in 2025? Industry needs to deliver this large #of dose 2015 ($1,100B) Creating a need for a strong cell therapy manufacturing ecosystem Source: Estimates based on data from ClinicalTrials.gov, Future Medicine, IMS Reports and internal research. * Prescribed medication healthcare costs

3 Fundamental changes required …
“The spiralling cost of new drugs mandates a fundamentally different approach to keep life-saving therapies affordable for cancer patients. We call here for the formation of new relationships between academic drug discovery centers and commercial partners, which can accelerate the development of truly transformative drugs at sustainable prices.” Workman et al. Feb 2017

4 Therapeutic evolution has been driven by biological discovery
Present Day Pre- 1900’s Small Molecules Biologics (e.g. monoclonal antibodies) Engineered Nucleic Acids (e.g. RNA) Natural Products, Blood Products Replacement Therapies (e.g. Insulin) Viruses, Viral-like particles, Gene Therapies Cells, tissues, & organs Combination therapies & regenerative medicines NOTE: Not drawn to scale

5 Cell Therapy: The administration of live whole cells or maturation of a specific cell population in a patient for the treatment of a disease. Source: What is Cell Therapy? It is not…… Regenerative medicine: A branch of translational research in tissue engineering and molecular biology which deals with the "process of replacing, engineering or regenerating human cells, tissues or organs to restore or establish normal function". en.wikipedia.org/wiki/Regenerative_medicine

6 So, is cell therapy really new?
Late 19th Century - Charles-Édouard Brown-Séquard injected animal testicle extracts in an attempt to stop the effects of aging. 1931 - Paul Niehans injected parathyroid cells from a calf to save the life of a patient who was in critical condition. The patient recovered and lived on for more than 25 years. E. Donnall Thomas - first human bone marrow transplant between identical twins, one of whom had leukaemia. Source: Wikipedia.org

7 Why the renewed interest in cell therapy?
2012 Diagnosed with ALL 2010 Emily was diagnosed with acute lymphoblastic leukemia (ALL) at age five in May 2010 and relapsed twice. After the second relapse, the Whiteheads were told they were out of options to treat her cancer. Not willing to give up, the Whiteheads pursued a radical new treatment called T-cell therapy at Children’s Hospital of Philadelphia (CHOP).

8 Autologous Cell Therapy: Personalised Cures
1. Cell Extraction 5. Therapeutic Delivery Hospital/Clinic 2. Selection/ Activation/ Modification 4. Therapy Dose Creation Centralized Manufacturing Facility 3. Cell Expansion 8

9 Allo vs. Auto Cell Therapy Production: Business models require different approaches
Allogeneic Universal Donor Autologou s Patient Specific Scale Up – Large Lot Sizes Scale Out – Massive Parallelism High start-up costs Master & working cell banks Production facilities and equipment Comparability Process control At-scale Risk Large batch failures Distribution Logistics Inventory management Precious starting material One “shot on goal” Non-destructive testing Chain of custody Patient heterogeneity Process variability Unpredictability High testing costs Massively-parallel processes Integration Scalability

10 Juno ditches lead CAR-T program following patient deaths
Juno Therapeutics has halted development of its lead CAR-T therapy months after patient deaths hindered the odds of success. The decision sees Juno switch its focus to JCAR017, a follow-up program that uses a defined CD4-CD8 composition company execs thinks will improve safety and efficacy. JCAR015 has appeared destined for the chop since patients died of cerebral edemas either side of a FDA clinical hold last year. But Juno held off on publicly ditching development of the CAR-T in adults with acute lymphoblastic leukemia (ALL) until this week. That delay enabled Juno to dig into the causes of the safety failings — which it thinks stem from rapid early CAR-T cell expansion — and set JCAR015 back to the extent that further work on a flawed candidate was deemed pointless. Source: fiercebiotech.com 02 Mar 2017

11 Gartner ‘Hype Cycle’ By Jeremy Kemp at English Wikipedia, CC BY-SA 3.0,

12 Process development requires deep process understanding and control
“Apprentice” model Process expertise Cell “look and feel” Focus on efficacy and safety “Scientific Management” model Managed processes Sample measurement Lean & Six Sigma reproducibility Focus on productivity & risk

13 What about production? Generic Workflow Repurposing bioprocess tools, blood processing tools, and/or basic research platforms Complex non-turnkey systems, limited standardisation Poor interconnectivity of workflow components Poor IT connectivity across workflow Scalability  regulatory implications Immature/incomplete supply chain Etc. Scale manufacturing process in an economically viable way for large patient populations

14 Therapeutic cell production today: Manual, disconnected & open process
Currently the process is very manual from connecting various tube sizes, moving products between systems and areas, measuring out small doses of media… There are many areas where a process break can occur, and the impact is huge. Images: gmpbio.org biosynergyeurope.com MIT Technology Review 118 (4) (2015)

15 Unit Operations in the T-cell therapy workflow
COLLECTION MODIFICATION EXPANSION HARVESTING THAWING & PREP Biosafe Sepax Media Biosafe Sefia SCT reagents Xuri Bioreactor, Media & Reagents Biosafe Sefia Biosafe Smart-Max

16 Aseptic physical connectivity – trivial?

17 Coping with variability?
D E Predictable Process A A C D E Shorter – issue? A A C D E Longer – issue? Aborted – Impact on patient? A A C A A C D E Ideal Time Planned availability

18 In silico process learning and monitoring
What are the required resources to process X patient samples per year that meet specified targets (cycle time)? 1 Ask the Question(s) Process Modeling Run Model Analyze Results Decision 2 Generic T-Cell Therapy Workflow 3 Key Assumptions: Process steps, resource requirements and task cycle times are defined # of samples per day, per week, per year Define constraint(s) Daily shifts are defined for the Operators and Verifiers Task times have no variability Etc. 4 Iterate 5 Hypothetical process simulation model

19 Smart cell processing: The Vision
January 14, 2018 Smart cell processing: The Vision Patient Product HW & SW agnostic connectivity Context aware data aggregation and feature extraction Unit operation analytics based on domain expertise Industrial Data Lake for Big Data storage Process wide Big Data analytics Prescriptive insights for process outcomes Raw material Subsystem Process Subsystem Process Subsystem Process Subsystem Process Subsystem Process Subsystem Process Subsystem Smart Bioprocessing Analytics subsystem(s) Industrial Data Lake HW & SW Agnostic connectivity: Not specific to GE equipment or software Feature extraction: Describe continuous curves (e.g. Chromatograms) by discrete points capturing the shape of curves Descriptive statistics: What happened? Predictive statistics: What will happen? Prescriptive statistics: Make it happen the way you want Process wide Critical Quality Attribute profile

20 Summary Clinical development and industrialisation is occurring in lock-step but have very different metrics Desperate need for process development understanding Improved process measurement and management Process risk can be minimized by: Simplifying processes Designing new unit operations Developing a robust supply chain Connecting Digitising Digital integration can be a powerful tool for process and facility design and optimization Smart analytics will lead to better and safer medicines

21 So, industrialising cellular therapies…
Is like: “Building the plane whilst flying it” (Phil Vanek) You must: “Keep the end in mind” (Marc Turner) Image: EDS.com And it is : “All about knowledge management – process development requires innovator and manufacturer collaboration” (Anne Black) Image: changingwinds.wordpress.com Image: mediafactory.org.au

22 “I find out what the world needs, then I proceed to invent it
“I find out what the world needs, then I proceed to invent it.” -Thomas Edison 22

23 GE and GE monogram are trademarks of General Electric Company
GE and GE monogram are trademarks of General Electric Company. Imagination at work, Predix, Xuri, are trademarks of General Electric Company or one of its subsidiaries. ©2017 General Electric Company—All rights reserved. First published March 2017 Xuri Cell Expansion Systems W5 and W25, Predix are not a medical devices nor CE marked and should not be used in diagnostic processes.  Drug manufacturers & clinicians are responsible for obtaining the appropriate IND/BLA/NDA approvals for clinical applications. GE Healthcare UK Limited, Amersham Place, Little Chalfont, Buckinghamshire, HP7 9NA, UK 23

24 Doctors at GOSH baffled when a routine cancer treatment failed
8 Young patients – 4 died Investigation by Michael Watts (UCL) GOSH had followed current best practice & established protocol (10 years). Standard viability check upon thaw "They looked absolutely superb. They were in good shape" Not routinely functionally tested - weeks vs hours "We were astonished when we got the function test results. The cells didn't grow properly.” Sophie Ryan-Palmer died a month after receiving the treatment Source: bbc.co.uk/news/health Accessed 09 June 2016

25 The wheels keep on turning…
Cellectis Gets U.S. Go-Ahead to Test 'Off-the-Shelf' Cell Therapy Feb 2017: Cellectis has won U.S. regulatory approval to run an early clinical trial using its gene edited cell therapy product UCART123 for blood cancers. Its first such "off-the-shelf" cell therapy UCART19, which is being developed with Servier and Pfizer, is now being tested in Phase I trials in Britain for acute lymphoblastic leukaemia and chronic lymphocytic leukaemia. It has already rescued two babies treated at London's Great Ormond Street Hospital from previously incurable cancer. Celyad Registers First Hematological Patient In CAR-T NKR-2 THINK Trial Feb 2017: Celyad’s lead candidate, CAR-T NKR-2, is a CAR-T-Cell engineered to express the human NK receptor, NKG2D, which is an activating receptor that triggers cell killing through the binding of NKG2D to any of eight naturally occurring ligands that are known to be overexpressed on more than 80% of tumors. The platform targets a wide range of solid and hematological tumors. Unlike traditional CAR-T cell therapy, which target only one tumor antigen, Natural Killer (NK) cell receptors enable a single receptor to recognize multiple tumor antigens

26 CAR T Cells More Powerful When Built With CRISPR Feb 2017: In a study published in Nature, researchers from Memorial Sloan Kettering Cancer Center reported that directing a CD19-specific CAR to a precise location in the genome of T cells using the CRISPR technology resulted in uniform CAR expression in human peripheral blood T cells and enhanced T-cell potency. The edited cells vastly outperformed CAR T cells generated using γ-retroviral vectors or other randomly integrating vectors in a mouse model of acute lymphoblastic leukaemia. Draper Looks to Ultrasound and Geometry to Reduce CAR-T Manufacturing Costs Feb 2017: The Charles Stark Draper Lab has developed two microfluidic prototypes to help make the manufacturing of cell therapies cheaper and more efficient. The devices address two key steps of the CAR T-cell therapy manufacturing process: the first uses an innovative acoustics approach to enrich the T-cells in a blood sample, and the second provides a new approach to gene transfer.

27 Patients Treated Per Batch
Whilst we can learn from bioprocess manufacturing, we are forging a new path Similarities to bioprocess manufacturing Requires cell culture technology Regulated as a drug Manufactured in sterile facilities Scaled production with automation Unique to Cell and Gene Therapy (Immunotherapy) Mass customization/parallel processing Critical custody management Care pathways connected throughout process Flexible factories (multiple products through same/similar line) May persist - potentially curative Complex distribution driven by product shelf-life $$$ Manufacturing Cost per Dose Biologics Viruses Cells Small Molecules $ Patients Treated Per Batch Cell manufacturing shares many features with the biologics industry. But the complexity of the cell versus the complexity of a protein or antibody, introduces some real production challenges. Cell viability, patient custody, cell characterization all are hurdles to be addressed.  Scale up Scale out 

28 The industry needs tool providers to provide de-risking technologies
Unit Operations Physical Integration Digital Integration Scalable Easy to use Smart - sensors embedded Modular Completely closed Low dead-space Exchangeable unit operations Manufacturer independent Facility independent Plug & play Unit operation agnostic Sensor enable everything Data dumps Connectivity through private clouds Data lakes for analytics Same as last slide.


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