Innovations in Oncology Trial Design & Development Webinar Series
Due to the complexity and uncertainty of oncology drug development, sponsors are faced with unique challenges and considerations when designing clinical trials.
Cytel's team of oncology trial design and advanced analytics experts are excited to host a series of complimentary webinars covering a range of innovative topics including adaptive design, machine learning, estimands and trial design software.
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Complete the form and select the webinars you'd like to attend. If you cannot attend please register and we will email you the webinar replay and slides.
Webinar Schedule
Key Design Considerations for Basket Trials and Umbrella Trials
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Jay Park, Director, Cytel
Transparent Machine Learning in Oncology
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Alind Gupta, Analytics Lead, Machine Learning, Cytel
Phase 1 Dose Escalation Trials with ESCALATE
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Pantelis Vlachos, Principal, Strategic Consulting, Cytel
A Clinician’s Perspective on Cancer Drugs Development
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Professor Martin Fey, Medical Oncologist
Conducting Sample Size Reassessment with Time-to-event Endpoints
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Pantelis Vlachos, Principal, Strategic Consulting, Cytel
Refocus Your Enrollment to the Subpopulation of Interest with ENRICH
Wednesday, May 13, 11AM EDT
Pantelis Vlachos, Principal, Strategic Consulting, Cytel
Oncology and Rare Disease
Thursday, May 14, 12pm EDT
Natasa Rajicic, Executive Advisor, Strategic Consulting
Estimands in Oncology
Thursday, May 21, 11am EDT
Monte Jarvis, Executive Advisor, Strategic Consulting
Descriptions
Key Design Considerations for Basket Trials and Umbrella Trials
Complete - Click here to watch the replay and access slides
Jay Park, Director, Cytel
With advancements in biomarkers and momentum in precision medicine, biomarker-guided trials such as basket trials and umbrella trials have been developed under the master protocol framework. A master protocol refers to a single, overarching design developed to evaluate multiple hypotheses with the general goal of improving the efficiency of clinical research. This webinar will introduce two master protocol types and explore their extension to design in various contexts from the HIV epidemic in global health to expedited oncology trials.
Transparent Machine Learning in Oncology
Complete - Click here to watch the replay and access slides
Alind Gupta, Analytics Lead, Machine Learning, Cytel
Machine learning (ML) aims to discover patterns from data that can be used for prediction. The use of “black-box” ML models in healthcare research and decision-making has been limited due to clinical liability and lack of trust from stakeholders. FDA guidelines for ML-based devices mandate transparency to assure continual safety and efficiency as notable recent failures have prompted increasing ML research into bias, fairness and causality.
Alind will present our continuing work in immuno-oncology using Bayesian network models for predicting safety and survival outcomes, extrapolating from limited follow-up data and validating with external real-world data for key subgroups. He will also present ways to incorporate subject-matter expertise and causality, and address ways to enhance transparency and communication for stakeholders.
Phase 1 dose escalation trials with ESCALATE
Complete - Click here to watch the replay and access slides
Pantelis Vlachos, Principal, Strategic Consulting, Cytel
This webinar will enable you to better characterize the maximum tolerated dose to improve your probability of success in later trials.
At the end of the webinar you will be able to:
- Simulate and analyse Phase 1 dose escalation trials for determining maximum tolerated dose (MTD)
- Understand a range of different methodologies that are used in Phase 1 dose escalation trials
- Communicate findings to the clinical team using East’s intuitive graphs and tables
- Simulate a dose escalation design followed by single-arm cohort expansion
A Clinician’s Perspective on Cancer Drugs Development
Complete - Click here to watch the replay and access slides
Professor Martin Fey, Medical Oncologist
The presentation will focus on medical oncology (surgery and devices out of scope) and will cover:
- Brief overview on treatment evolution
- Remaining issues of side effects of immunotherapies
- Clinician perspective on endpoints (e.g. statistically significant does not mean clinically meaningful)
- PRO and patients perspectives, evolving health authorities perspective
- Biomarkers
The speaker will use different examples of oncology trials during the presentation.
Conducting Sample Size Reassessment with Time-to-event Endpoints
Complete - Click here to watch the replay and access slides
Pantelis Vlachos, Principal, Strategic Consulting, Cytel
This webinar will provide an overview of the SURVIVAL and SURVADAPT modules. Dealing with time-to-event endpoints, this will enable you to increase your sample size when your results look promising but lack the targeted power.
At the end of the webinar you will be able to:
- Use simulation tools to illustrate complex survival data at the design stage
- Explore trade-offs between duration and patient accrual, choice of boundaries, spending functions and hazard functions
- Utilize the promising zone to determine increases in sample size given information acquired during the trial
Refocus Your Enrollment to the Subpopulation of Interest with ENRICH
Wednesday, May 13, 11AM EDT
Pantelis Vlachos, Principal, Strategic Consulting
This webinar will teach you how to simulate an adaptive population enrichment design with a survival endpoint, which enables you to decide whether to continue enrollment in both sub-populations with or without sample size re-estimation, only continue enrollment from the sub-population of interest, or terminate the trial for futility.
At the end of the webinar you will be able to:
- Simulate a population enrichment design with a survival endpoint
- Understand the 5 different zones used in adaptive population enrichment design
- Utilize different zones to make decisions regarding adaptation on sample size and patient population
Oncology and Rare Disease
Thursday, May 14, 12pm EDT
Natasa Rajicic, Executive Advisor, Strategic Consulting
Limited patient populations that result in small study sample sizes is typically seen as the key difficulty associated with the development of therapies for rare diseases. Other hurdles often present when studying rare diseases include uncertainties around disease history, target patient profiles, and the existence of appropriate comparators. Further complications may arise when developing novel therapies and disease targets where the choices of the most appropriate primary endpoint(s) is unknown or not well established.
In this webinar, we will provide examples of clinical development issues and possible solutions from studies in rare diseases, including rare cancers.
Estimands in Oncology
Thursday, May 21, 11am EDT
Moderator:
James Matcham, Sr Principal, Strategic Consulting, Cytel and former VP Early Biometrics and Statistical Innovation, AZ
Panelists:
Michelle Casey, Executive Director of Biostatistics, Pfizer
Kaspar Rufibach, Biostatistician, Roche and member of the Estimands in oncology SIG sponsored by PSI and EFSPI
Rob Hemmings, Partner, Consilium and former Chair of CHMP SAWP and head of Statistics at MHRA
Andy Stone, Director, Stone Biostatistics
Paul Terrill, Principal, Strategic Consulting, Cytel
After the ICH introduction of the Estimand framework for clinical trials in ICH E9(R1), finalized in November 2019, regulatory authorities are requiring detailed Estimand statements in trial protocols. This requires the pre-definition of the four Estimand Attributes (treatment, patient population, variable, population-level summary) and the Estimand Strategy for addressing inter-current events. In Oncology studies, defining the Estimand framework for time to event endpoints is particularly challenging, for example due to different censoring strategies for intercurrent events and their corresponding implications.
Join us for a complimentary virtual panel discussion with regulatory and industry experts, who will be giving:
- A short presentation on Estimands in Oncology Trials
- A discussion on the issues around the practical implementation of the Estimand framework in Oncology