For life sciences organisations, the pressure to speed up the time to market of new drugs and therapies continues at pace, alongside the need to reduce the cost of doing so.
What is needed is a new technology paradigm that will reinvent the life sciences business model by connecting data, knowledge, people, and insights.
Quantum computing
Pharmaceutical Research and Development is now replete with fields of research that offer potential use cases for quantum computing.
These include quantum simulations for molecular design, molecular similarity, protein folding and protein-ligand interactions.
Other applications include the modelling mechanisms of drug action, biomarker discovery, quantitative structure activity relationships, and modelling the behaviour of larger biological systems.
More broadly, pathology and image analysis, precision and personalised medicines and genetics –particularly linking our personal genome through cell and gene therapies to radical new health outcomes –all involve complex computational systems that would benefit from quantum computing.
The best way to chart a course forward is by looking at the recent past.
Huge improvements in computing power have already made the practical deployment of AI for solving complex problems a realistic possibility.
From image data analysis to evaluate the molecular structure of a compound, to making diagnoses by analysing radiology data, AI use has seen rampant growth and improvement in the last 24 months.
This progress has prompted substantial investment and significant partnering and acquisition activity, including between major pharmaceutical companies and leading AI providers and start-ups.
All this activity is opening the door to new configurations between life sciences firms and hyper-scalers, leveraging massive computing power and mastery with data.
Quantum computing could follow a similar trajectory, with systems capable of practical deployment in R&D being a realistic possibility by 2035.
Securing genetic jewels
Even with new modes of development and production, old challenges remain.
As the quantity and quality of data increases to meet the new personalised and precise form of medicine, so too will the threat of security breaches.
Today, it’s difficult to imagine hackers running off with the code that makes up an entire human being—but history shows us, little is safe.
Similarly, new processing power—particularly quantum—stands to challenge even today’s most robust security protocols.
In the future, the entire healthcare ecosystem will spend considerable resources designing and managing complex, interconnected networks that are likely to face constant attack, and from toolsets that move from helping the sector, to harming it.
While the quantum revolution may still be a decade away, these trends have a habit of rapidly advancing at a faster pace than expected: take the rise of generative AI as an example.
On the road to the quantum revolution, businesses should focus their efforts on the following:
Replicate the agility of startups
Large companies can respond to a rapidly changing landscape by adopting the culture and operating models of small-cap firms and start-ups.
This entails fostering a culture of innovation, adaptability and rapid decision-making. Crucially, the speed at which small-cap firms are able to mobilise around new innovations and products is disrupting the market at large.
In 2022, 65% of new drug approvals were granted to small and mid-sized biopharma companies, significantly outpacing large pharmaceutical manufacturers. 2023 is on track to see more upstart companies outpace legacy pharmaceutical brands.
Measure what matters
It’s crucial for companies to regularly evaluate their investments and ensure they align with industry-wide priorities.
Large companies should assess the agility of their application estate to ensure they are prepared to take actions such as divesting underperforming units or acquiring fast-growing segments to remain competitive, in a timeframe that makes the ROI of the decision worthwhile.
Build a decision-making framework
Companies should establish a robust decision-making framework to effectively navigate the dynamic technological and business landscape – identify trends to invest in and determine the necessary platforms and partnerships to succeed.
Customisability is key; the framework should be adaptable to the company’s unique operations. In a rapidly evolving market, these frameworks aid in making informed decisions and ensure alignment with the company’s operations and objectives.
Break down siloes and institutionalise resources
Businesses need a greater balance between a high degree of autonomy in business units and a centralised ability to ensure skills and resources flow to areas of the business where they can provide the most value.
This approach optimises resource allocation and enables the development of strategies that benefit multiple value streams.
For example, a single platform like generative AI can be used across different business areas to enhance outcomes and reduce resource consumption—rather than each siloed business unit embarking on their own journey.
Develop organic strategies
Companies can address unmet industry needs by developing internal organic development capabilities to find solutions to challenges where no existing answers are available – building solutions in-house where possible, and then examining new commercial opportunities.
This approach not only solves internal challenges but also generates additional income. Companies should be proactive in identifying unmet needs within their industry and building solutions that can be monetised.
The next decade will present as many opportunities as challenges for the rapidly evolving life sciences sector.
While today the focus remains on dealing with immediate waves of economic uncertainty, leaders in the sector cannot hold back on vital transformation work.
Slowing progress on building critical digital foundations today will have an outsized impact on a company’s ability to perform, especially as new expectations for personalisation crystalise and ecosystems of highly interconnected organisations develop.
Rohit Alimchandani is Head of Life Sciences for UK&I at Cognizant
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