Explainambiguity Think Tank is part of the Drug Target Review Advisory Board
Explainambiguity Think Tank is dedicated to addressing the complexities and ambiguities inherent in the integration of Artificial Intelligence (AI) within the pharmaceutical and healthcare sectors.
Our mission is to provide clarity, foster innovation, and ensure regulatory compliance by tackling the root causes of ambiguity in AI applications. By doing so, we aim to drive business success through enhanced transparency, trust, and efficiency.
Join us in our mission to clarify the ambiguous, ensuring a safer, more efficient, and innovative healthcare landscape. Together, we can transform challenges into opportunities for growth and improvement, driving business success through AI clarity.
Sept 18, 2025 - 03:00PM CEST CLICK TO REGISTER
Making sense of AI: bias, trust and transparency in pharma R&D
Drug Target Review · September 11, 2025AI is increasingly used in drug discovery, but hidden bias and ‘black box’ models threaten trust and transparency. This article explores how explainable AI can turn opaque predictions into clear, accountable insights.The rise of multimodal language models in drug development
European Pharmaceutical Review · June 12, 2025Industry experts, Remco Jan Geukes Foppen, Vincenzo Gioia, Alessio Zoccoli and Carlos Velez reflect on the necessity to ensure data quality in order to gain full advantage from multimodal language models (MLMs).From siloed data to breakthroughs: multimodal AI in drug discovery
Drug Target Review · June 11, 2025Drug development has long been hindered by fragmented data and complex processes, but a new wave of AI is reshaping the landscape. By integrating genomic, clinical and molecular data, multimodal models are revealing hidden patterns and accelerating more precise advancements in medicine.