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Leading the Way in Effective Drug Development

Digital Tech
Mar 07, 2022

Good Machine Learning Practice: The First Step Toward Transparency & Trust

Machine learning (ML) innovation in healthcare is growing, and the oversight on its development should keep pace to ensure it’s developed in a scientifically sound, safe way. Just as the FDA requires detailed ingredients on the side of cereal boxes to help consumers make informed health decisions, the same transparency should apply to the ML technology our patients and clinicians use every day to make informed care decisions.

Company 3
Feb 22, 2022

Mitigating Bias in AI: Holding Innovation to a Higher Standard

When it comes to building equitable, quality AI, prioritizing diverse data sets needs to be embedded in a developer’s DNA – rather than a “nice to have,” it should be a deliberate framework in which AI is built.

Adobe Stock 436772841
Feb 01, 2022

Why Diversity is one of AiCure’s Founding Principles

AI has great potential to transform drug development and patient care as we know it – from elevating a clinical trial’s data to speed up research, to supporting clinical decision-making to drive confident care.

DBM Woman
Aug 18, 2021

AI in Clinical Research is On the Rise (and More from DIA 2021)

Each year, thousands of professionals from across the pharmaceutical industry come together to share data and ideas at the Drug Information Association (DIA) conference. This year, AiCure wanted to leverage the collective experience of those attending DIA to gain insights into how the industry views its evolving use of advanced machine learning and artificial intelligence (AI) technologies.

Patient Connect
Jun 29, 2021

Personalization, Patients And Product Management — An Experiment In Caring

I’ve worked in product management for 20 years or so and I’ve grown accustomed to people not understanding what I do. I’m pretty sure my father in-law thinks I code websites. My friends think I build mobile apps. I stopped trying to explain my job to my wife and kids except in the vaguest terms.

Card1
Jun 01, 2021

Testing the Power of Predictive Analytics and AI

There are many reasons why patients might be nonadherent – whether it’s study fatigue, forgetfulness, or juggling other responsibilities and stressors. Despite the best efforts of site teams to identify the most qualified and motivated patients, ensuring treatment plan compliance over the course of an entire study has continued to impact data quality and study performance.