The use of medical imaging biomarkers to better understand the efficacy of cancer drugs, aided by the power of AI.
Oncology clinical trials would benefit greatly from new biomarkers that could help to better understand the efficacy of drug treatments. Growth rate (‘g’) of tumour derived by appropriate tumour growth rate (TGR) modelling, as well as quantitative estimation of tumour heterogeneity through radiomics are two processes that offer such oncological imaging biomarkers.
Response evaluation criteria in solid tumours (RECIST) 1.1 and other similar criteria for tumour burden assessments have been used conventionally for the investigation of the tumour-inhibitory effect of cancer drugs. A large sample size is commonly required for both a reliable estimation of overall survival from such criteria, and to differentiate from the control arm. However, the ‘g’ value obtained through effective TGR modelling may provide a more efficient alternative to understanding drug efficacy using a lower sample size.
Radiomics is the extraction of quantitative metrics from medical images that characterise tumour heterogeneity. Radiomic features (both cross-sectional and longitudinal changes) have been associated with tumour aggressiveness and may predict clinical and clinical trial endpoints like survival.
In this webinar, we will discuss the basics of TGR modelling from oncological imaging data, as well as radiomics. We will also look at how AI can be harnessed for a more automated tumour volume detection, and how this can aid with simultaneous assessment of both ‘g’ as well as radiomics features.
Paul McCracken, PhD, Vice President, Global Head of Medical Imaging, ICON
Dr. Paul McCracken is the Global Head of ICON Medical Imaging. Paul has over 20 years of experience in imaging and pharmaceuticals, with a strong track record of applying imaging and biomarkers to drug discovery and development across a range of therapeutic areas.
Ramkumar Krishnamurthy, PhD, Medical Imaging Scientist II, ICON
Dr. Ramkumar Krishnamurthy is a Medical Imaging Scientist and MRI Physicist with over 15 years of clinical imaging experience, including body and cardiovascular imaging. He was also the technical manager for the advanced imaging clinical lab for many years, working with advanced processing of imaging data, including tumour imaging metrics.
Meena Makary, PhD, Medical Imaging Scientist II, ICON
Dr. Meena Makary is a Medical Imaging Scientist with over eight years of clinical imaging experience including multimodal neuroimaging and AI. Prior to ICON, he completed his postdoctoral fellowships at Yale and Harvard Universities for four years focusing on understanding the neural basis of several psychiatric and neurodegenerative disorders. At ICON, Dr. Makary is working on developing advanced imaging analysis tools and AI algorithms.
Who Should Attend?
Studying ‘g’ and radiomics features at the initial phases of drug trials may help the study team gain early insight into drug efficacy. This webinar will be helpful for all who are involved in the study design of drug trials, especially:
- Medical Directors
- Imaging Scientists
- Operational Leaders
What You Will Learn
Attendees will learn:
- The need for reliable estimation of the inhibitory effect of oncological drugs using lower sample size
- Various models for estimation of tumour growth rate (‘g’), including exponential models
- The value and pitfalls of tumour characterisation using radiomics
- The advantages of volumetric assessment of tumour size when compared to conventional line measurements
- How the power of AI can be harnessed to facilitate better extraction of tumour volume
ICON is the world’s leading clinical research organisation, powered by healthcare intelligence. From molecule to medicine, we advance clinical research providing a comprehensive suite of outsourced development and commercialisation services to pharmaceutical, biotechnology, medical device and government and public health organisations. We develop new innovations, drive emerging therapies forward and improve patient lives. Our outsourcing models can be adapted to suit small local trials to large global programs, including full service, standalone services, FSP and full asset development.
With headquarters in Dublin, Ireland, ICON employs approximately 41,150 employees in 113 locations in 53 countries.