AI: A key enabler for start-ups?

In the Life Science space, we are frequently seeing innovative start-ups raising investor funds based on emerging technologies, specifically artificial intelligence (AI). Investment in AI-focused start-ups by VCs has soared since the early 2000s.

As the Life Sciences industries evolves towards value-based systems and stakeholders become more demanding, start-ups are increasingly looking to embrace AI and data analytics to substantiate value and deliver better outcomes.

These trends are quickly becoming fundamental elements of business strategy for many life science start-ups. Becoming a sustainable ‘AI-powered’ start-up in the industry will continue to require powerful financial backing to enable the recruitment of data specialists and improve technologies, eventually leading to the scale up and ultimately widespread adoption.

The most ambitious in this space recognise the need to continually innovate and establish their product-market fit and plan ahead for funding, while also utilising strategic partnerships and business development approaches to deliver that essential growth & ultimately, return on investment.

Implementing AI

Many leaders of life science start-ups anticipate that the application of AI to their business will be a massive undertaking, involving full-scale organisational transformation. However, in our experience the very best way to capitalise on AI is to start small, but with highly targeted use. Below we look at just a few of the areas that a little AI can make an impact:

The Case for Med Tech

AI can help Med Tech to save lives by increasing diagnostic accuracy, enhancing surgical precision and patient management.

  • Diagnostic Accuracy: AI’s use in diagnostics is already benefiting patients by helping to identify diseases more accurately.
  • Surgical Precision: The operating theatre is finding value in AI, utilising it to improve surgical outcomes. By offering real-time data insights, AI provides the visibility and accuracy to help surgeons improve their movements throughout procedures and determine follow-up analysis.
  • Real-Time Patient Health Management: People’s lives today revolve around smartphones, and the extensive amount of personal data already being collected via our smartphones can benefit patients and doctors by helping to virtually manage PoC.

Clinical Trials

AI-powered tools could help revolutionise clinical trials, thanks to their ability to analyse patients’ electronic medical records anonymously, cross-referencing hundreds of available trials based on specific criteria. The challenge of analysing and drawing conclusions from this massive data set in real time is physically impractical for medical teams. AI can use the data from these records to better identify probable fits for clinical trials, leading to improved protocols and patient recruitment/retention numbers, more accurate time scales, and lower costs. AI also can increase trial success rates by finding patterns across symptom progression and outcomes.

Drug Discovery

AI can speed up drug discovery by improving workflow. Automating data management and streamlining the data-heavy process of drug development leads to clearer, more targeted results. Integrating data with workflow management to improve efficiency ultimately reduces the cost of drug discovery.

AI holds the promise of reforming the life sciences industry, which is well-positioned to benefit from the new insights it proffers. That said, it should be acknowledged that right now, AI is still in its infancy and start-ups should remain agile & remain flexible and as the space continues to evolve to make the most of what it currently offers.


Beyond successful technical strategy and product-market fit, growing a life sciences startup involves funding. Determining the ideal source of capital to help fund growth can be difficult — but it also can lead to greater long-term success. Life sciences startups have many channels available to raise capital at various stages, each with their own advantages and concerns to contemplate. Founders must understand which asset class will strategically address their unique needs and support their success, while also realising that their funding needs will change at each growth stage.

  • Incubators or accelerators can be a good option for early stage startups. Many can provide incredible facilities for much less than the cost of building your own state-of-the-art laboratory. The key factors when determining which incubator is right for you include the occupancy term options, subvertical specialties, resource needs, and quantifiable costs.
  • Family offices are becoming more active in the life sciences landscape. For a startup seeking capital, a key advantage of working with a family office is the lack of constraints. Without board representation or control, family offices are more agile in investment management, which makes them a natural fit for early-stage funding.
  • Corporate investors typically invest directly in startups to foster technological development. While they often have the goal of eventual merger or acquisition, they may also pursue investments for pure ROI or competitive advancement, making corporate venture capital a suitable avenue for many growing startups.
  • Crowdfunding is particularly beneficial for life science startups with a strong emotional tie-in, as backers do not have any financial returns tied in with their contributions. It needs, however, to have mass market appeal, and so this option could work well for a patient-focused cancer care mobile platform, for instance, rather than a lab-based clinical analytics software.


  • International Expansion: Increasingly, life sciences startups are considering international expansion at earlier stages of the business life cycle to tap into new markets, gain access to innovation and technology, better serve local needs through global operations, and increase cost savings. It is also pragmatic to think strategically about the different value that a start-up’s products and solutions may hold in different regions when developing an expansion plan.
  • Balance Agility and Scalability: Building momentum for an innovative life sciences solution often involves the need to scale up, but maintaining the agility that defines a startup is crucial to scaling successfully in this industry. In a dynamic, evolving market where life sciences companies are increasingly investing in development and the manufacturing chain, how do these companies remain nimble and proactive when opportunities to expand the scope of the business present themselves? Utilising the latest technological advances in development, design, and manufacturing, while also investing in key talent that can help maximise the investment in these technologies, can help companies remain agile and in front of a changing market landscape — attributes that are vital to long-term sustainable growth.
  • Diversify Offerings: Founders should carefully contemplate their asset diversification strategies as they evolve their business. Benefits to diversification include having multiple opportunities to succeed in each market by spreading the startup’s core technological advantages across different applications. This also helps with the financing landscape and with risk mitigation in a clinical setting, as success or failure is not beholden to one individual pathway. A well-diversified company can sensibly evaluate results and terminate weaker solutions, while building out optimal paths to market.

If you would like to confidentially discuss how Norman Broadbent Group could help you overcome your business or people challenges, please contact Nick Behan on +44 (0) 0207 484 0106 or via