During Discovery Week 2021, Ian Churcher (Chief Scientific Officer at Amphista Therapeutics Limited) gave a fascinating presentation on recent advancements and novel approaches in protein degradation. This article provides a condensed overview of the key topics covered.

Cellesce develops bioprocessing systems for the expansion of organoids in significant volumes in a way that minimises handling time and maximises reproducibility, with the long term goal of positioning organoid technology as a cost effective model for early-stage drug discovery.

Dr Boris Adryan, Digital & Data Capability Building Lead at Merck Healthcare KGaA, teaches the company’s workforce the importance of data.

This Commentary piece looks at the means by which the global approval process for new medicines can be sped up through the controlled use of FAIR data. Key areas of focus include the sharing of healthcare data to bring the patient voice within the clinical setting.

This Commentary article revisits the development and implementation of mobile health data, exploring how initiatives such as the NHS track and trace system helped to mitigate the worst of the impact of the Covid-19 pandemic. Here, we consider the applications of mHealth data for present and future pandemic situations.

Key opinion leaders discuss the latest trends and challenges in laboratory automation and digitalization. Key insights include an explanation of Roche's 'Levers of Production' method, the challenges of legacy systems and the possibility of digitalization overload.

How are AI integration and the growing capabilities of machine learning impacting drug discovery and clinical trials?

Artificial intelligence and machine learning could be an invention comparable to electricity, so what does the future hold for its use in drug discovery?

There are many reasons why it is crucial to understand how an AI-enabled system has led to a specific output. Explainability can help developers ensure that the system is working as expected, meet regulatory requirements, or reveal the importance and effects of data previously deemed unimportant by humans.

Some of the biggest current focuses of machine learning and AI research and development include testing clinical scenarios to identify the patients who will benefit most from treatment. One of the main goals for researchers is increasing the transparency and understanding underpinning data sharing and AI technology.

The pharmaceutical industry is working on improving the usability of automation platforms but challenges remain.

One of the most impactful advances in stem cell research of the past decade has been the development of organoid culture techniques.