Drug development and rapid innovation are unlikely bedfellows.

Drug development is, by its very nature, a long-winded, wieldy, hyper-expensive process. However, the integration of artificial intelligence, high-throughput screening techniques, and advanced computational modelling has catalysed the identification of potential drug candidates and expedited the prediction of their efficacy and safety profiles.

Are we finally entering an era where the once-distant notions of drug development and rapid innovation are becoming increasingly intertwined? And what will it take for the industry to fully harness the potential of novel tools and strategies to address unmet medical needs in a more efficient and agile manner?

In 2022, the US’s National Academy of Sciences, Engineering & Medicine (NASEM) released a damning report into underrepresentation in clinical trials.

"While progress has been made with representation of white women in clinical trials and clinical research, there has been little progress in the last three decades to increase participation of racial and ethnic minority population groups."

Whilst we celebrate diversity in Europe, from race to gender, sexuality to age, participants in clinical trials remain overwhelmingly white and male. However, until interest and investment to improve diversity and representativeness in trials comes to the forefront, the goals of diversification remain poorly articulated and understood.

We all know how important diversity is, but how exactly can we make clinical trials attractive to all?

We’ve all done it.

You get an odd rash, or a strange pain in your back, and off to the internet you go.

But googling your symptoms only tells you which diseases have the best SEO. There are pros and cons to googling your symptoms (or Binging them, if you’re really alternative), but in this interconnected world, where access remains an issue, the number of people doing it will continue to rise.

How can we ensure that search engines prioritise accurate, accessible, and up-to-date health information, and steer those in need away from misinformation?

Dr. Google will always be faster and more accessible than traditional healthcare systems. Maybe, in fact, search engines are exactly what the doctor ordered.

In the past, the idea that technology could offer earlier detection and prevention of diseases, unparalleled insights into diseases currently not tracked well with diagnostic tests, and improved patient engagement, safety and quality of care, would have been laughable.

On the face of it, digital biomarkers are the holy grail, beautifully blurring the patient-consumer boundary, and providing clinicians with previously inconceivable levels of monitoring and data, and patients a level of health autonomy never previously possible. But there is no perfect fit.

Lack of precision, gaps in both evidence requirements and economic models, and questions around data ownership abound. Can digital biomarkers rise up to the expectations?