Persistent Challenges in Computational Biology
Computational biology is an interdisciplinary field that drives innovation across drug discovery, diagnostics, and healthcare. It is fuelled by diverse data generated by new technologies (e.g. single cell, spatial omics), constant progress in computing power and rapid development of AI-ML approaches. However, translating analyses or turning models into real-world and impactful outcomes remains hard.
Persistent challenges include:
- integrating diverse data, (e.g., omics, clinical, image)
- data standards
- appropriate benchmarking of methods (as well as a deluge of them)
- ensuring reproducibility, and bridging gaps between computational teams and decision-makers
- integration of computational teams with experimentalists and implementation of “lab-in-the-loop” principles
Many tools come from academic or research settings, where the focus is on innovation rather than industrial deployment — as a result, such tools encounter challenges around validation, deployment, infrastructure, and regulatory readiness.
Talent shortages and adoption hurdles further slow progress.
This Pistoia Alliance Life Science Informatics Forum will explore not just the scientific frontiers, but also the practical, organizational, and cultural shifts needed to overcome these challenges — helping to improve the efficiency and effectiveness of computational biology.
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Please note, places for this event are limited. Please fill in the form below to register your interest in attending.
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