22 Oct Interview Questions For Gertjan Bartlema of Celularity, Inc.
Gertjan Bartlema, is the Executive Vice President, Corporate Strategy and Business Development at Celularity, Inc. Previously he served as Vice President, Information Knowledge Utilization at Celgene Corporation in New Jersey and held positions as General Manager Middle East, Africa & Greece and Executive Director Marketing & Sales Excellence for Celgene EMEA, based in Switzerland. He was a member of Celgene’s Business Development team that acquired Gloucester Pharmaceuticals Inc. and Abraxis BioScience Inc. Read his full bio.
Interview Questions For Gertjan Bartlema of Celularity, Inc.
Q: Artificial intelligence (AI) techniques have sent vast waves across healthcare, even fueling an active discussion of whether AI doctors will eventually replace human physicians in the future. Do you believe that human physicians will be replaced by machines in the foreseeable future? What are your thoughts?
A: In my opinion, physicians will not be replaced by machines in the foreseeable future. Machines and technology will become more embedded in healthcare practice to augment intelligence and decision making, leading to faster diagnosis and efficiency.
Q: Can you provide some use cases that have already successfully demonstrate the value of AI/Machine Learning in healthcare?
A: Signal detection efforts in pharmacovigilance, access to EMR data and use for comparable patient (synthetic) cohorts, treatment decision support and optimization based on patient cohort comparators.
Q: What areas in healthcare will benefit the most from AI/Machine Learning applications and when will that be?
A: Near term automation could play an important role for those routine tasks that take time away from healthcare practitioner – patient interaction. Predictive analytics and treatment decision support will benefit more through a growing awareness of necessity of common data models and data standards which will contribute to broader utilization of real world data.
Q: What are some of the challenges to realize AI/Machine learning in healthcare?
A: Need for standardization of data, use of common data models, and practice of data sharing (consolidation of EMR vendors might help as well). Without these, broader application of AI/machine learning will continue to be a hype.
Q: How close are we with successfully using AI for the purpose of mining big data?
A: Depends on the expected outcome and/or objective. Impacting patient benefit through better treatment decisions and outcomes is imminent.
Q: What is your outlook or vision for use of AI/Machine Learning in healthcare?
A: Great opportunity to make a lasting impact on healthcare and benefitting patients as long as we can move on from the hype! There needs to a continued focus on the enabling foundation (data standards, common data models) required to allow AI/machine learning to create blossom.
Q: If AI is not quite there yet, what is needed to get us there?
A: Focus on the foundational elements of data standards, common data models and data sharing.
Q: Is there anything you would like to share with the PMWC audience?
A: A collective impact approach and continued multi-stakeholder collaborations is going to be key to leverage the advances in technology for the advancement of patient care.
