How Technology And Economic Uncertainty Is Impacting The Life Sciences

By Lisa Om, VP of product marketing at USDM Life Sciences

The pandemic hit life science companies hard, and just as they started to stabilize, a new wave of macroeconomic challenges is crushing the industry. Threats of a looming recession make funding hard to come by, and along with high inflation and increasing energy costs are compounding the already significant financial pressures.

Along with that, technologies like artificial intelligence are evolving at a faster pace than expected. While pharma companies are taking advantage of these solutions to drive innovation forward, there is now an exorbitant amount of data that pharma and life science companies need to manage. And unlike other industries, those in life sciences need to meet complicated regulations to manage this data properly, and many don’t have adequate infrastructure in place. Nor do they have the means to set it. So, how did life sciences get here? Here’s what led to this industry-wide knot that needs to be untangled.

Poor People Management

The tech industry increased its layoffs by 649% in 2022, which is the highest since the dot-com bubble more than a few decades ago, according to "The Challenger Report". This is reflective of poor people management during the pandemic. Many companies, including life science players, went into a reactive mode and did not think of long-term planning when rearranging their business structures due to the pandemic’s impact. The future was uncertain, and anything connected to the tech industry started booming. 

This led to over-hiring, impulsive investments, and hasty restructuring. But as 2023 kicked off, many leaders realized that they were dealing with limited funds and a surplus of staff. Along with that, accelerating technology, such as generative AI, streamlined functionalities, making it so fewer people could do more work. 

Companies emerged from the fog of the pandemic, but it was clear that reactive mode was no longer needed. It also became apparent that businesses must streamline operations to drive greater efficiency if they want to thrive financially. 

Bank Collapses 

The bank collapses have reverberated across the industry. Many pre-commercial, startup biotech companies experienced liquidity problems after the collapse. This increased pressure on all financial investments because these companies have very little flexibility, and there is no room for mistakes. Every dollar counts. 

Companies have had to review their spending and not allow critical research and clinical trial deadlines to be missed – now, projects must be on time and within budget. And startup biotechs are experiencing more pressure than others because they have longer go-to-market timelines. It can often take years before a drug, new therapy, or medical device starts generating revenue and providing a return on investment. 

This is something that’s going to have a continued impact, creating even more hesitation for investors to give their hard-earned dollars to these types of companies. Life sciences businesses are trying to figure out how to do more with less and are focusing their resources on the most promising discoveries in their journey to commercialization. 

Regulatory Issues 

Regulators are just now catching up with many modern technology systems. One example is cloud-based systems that don’t have traditional installation and deployment barriers of on-premises solutions to prove they operate as intended. Computer Software Assurance is an initiative the FDA is moving forward to evolve the requirements for how computer systems that impact a product or patient safety incorporate modern cloud technologies and create operational efficiencies. 

Another example of this is the rise of generative AI. Data inputs determine its power, so if bad inputs equal bad outputs, proving accuracy is a hurdle. And with such massive amounts of data, pharma companies haven’t quite figured out how to make use of large language models given the nature of the specialty work required to make the outputs valuable. More challenging is that the data is constantly changing, faster than ever before, so how do organizations establish ownership of said data? How do they protect their data and intellectual property from being absorbed into generative AI platforms? Regulators don’t have any of the answers yet.

While there are so many unknowns, one thing is clear - regulators and health authorities have a responsibility to ensure the safety of the people using new technology and products.

Future Trends

Currently, companies are struggling with a pandemic hangover. Many have spent the last couple of years hiring with no long-term plan, deploying technologies without a strategy or governance in place to enable remote workforces, and making rash decisions to maintain business continuity. 

But now, the same companies that at the start of the pandemic needed to deploy compliant eSignature systems in a week require help consolidating and optimizing their technologies for maximum efficiency, productivity, and ROI. Everyone is trying to do more with less. 

It is the time for life sciences to make better people, process, and technology decisions. This means having the right systems at the right time in their commercialization maturity, the best talent to achieve their goals, and processes that ensure they stay in compliance and deliver high-quality products so that requirements like validation enable innovation, not slow it.

Starting with the end in mind is essential. Businesses can save a lot of time, money, and headaches by enlisting advisors to help identify challenges they’ve never considered and prioritizing strategic planning to create better decision-making and operational efficiency down the road. The industry moves so fast, and it’s hard to find time to think critically about everything that is happening. Yet, it is crucial to get the best minds together and do collaborative, strategic thinking. Technology can’t do that.