Pacesetters

Transformative AI trends and race to stay relevant

Leading organisations are in the first mile of a marathon that is poised to transform the business of health.

Why are these change imperatives such a priority now? A confluence of cutting-edge technologies, ethical imperatives and patient-centric strategies is steering the industry towards safer, more effective care.

Organisations with the strategy and skills to move now will set a course for differentiated growth in years to come.

The transformation is fuelled by more accessible AI and generative AI, cost management, ethical innovation and patient equity. But how will it unfold?

A standout driver is the widespread embrace of generative AI capabilities in life sciences. Organisations are now deploying multiple pilot use cases and establishing expertise in the safe and compliant use of this transformative technology.

From document generation to drug discovery, generative AI is proving to be a catalyst for enhanced productivity, efficiency and, most importantly, accuracy.

Alongside, there is a critical need for trustworthy automation, optimisation and governance with challenges posed by AI technologies’ misuse (e.g. cyber attacks), emphasising the industry’s commitment to building trust through ethical practices.

From a healthcare standpoint, there are also hurdles in realising the value of AI. The year ahead is set to be marked by substantial changes driven by large language models and AI technologies.

Clinical documentation, early detection and personalised medicine are poised for significant advancements, presenting operational, talent, financial and value-related challenges.

The rise of personalised medicine, for example, is reshaping the production of medical therapies by emphasising targeted treatments based on individual characteristics.

This trend is leading to the development of precise, biomarker-driven therapies and the integration of companion diagnostics to identify responsive patient populations. Clinical trials are now often designed to stratify patients, enhancing efficiency and treatment assessment.

Pharmaceutical companies are investing in advanced data analytics to glean insights from diverse data sources, while regulatory agencies are adapting guidelines to accommodate these challenges.

This shift is not only influencing drug development but also posing supply chain challenges, requiring adaptable manufacturing processes for therapies tailored to smaller, specific patient groups.

For a number of public policy and macroeconomic reasons, cost management in healthcare will play an even greater role in determining organisational success in the next 24 months.

The challenges posed by price transparency rules and the shift towards value-based care necessitate innovative approaches and the strategic use of advanced analytics.

In the US for example, price transparency rules are forcing insight that allows patients and healthcare consumers to be more decisive about their treatment options.

And because of that, consumers are asking tough questions that the ecosystem hasn’t historically had to deal with.

Organisations are having to dig in a little bit further to have a better understanding of the true value that their products provide.

To be able to articulate that value in a data-based manner is becoming essential, and for that, it’s key that the right technology is deployed to answer those questions.

We are also seeing a deeper approach to patient engagement focused on making access to healthcare technology more equitable.

Many are calling this ‘techquity’ and welcoming a broader approach that incorporates patient engagement, diversity, inclusion, access to care and technology.

From the design of tech-deployed therapies to the management of decentralised clinical trials, the choice of tech platform impacts the percentage of the population whose needs can be met.

Ultimately, ensuring these tools benefit everyone equally is vital. 

Alyssa Farrell is Director, Health and Life Sciences at SAS. Go to SAS.com