As healthcare and biopharmaceutical companies embrace artificial intelligence, insurance underwriters see risks and opportunities
The development of precision medicine has transformed the life sciences industry. The identification of disease-associated biomarkers and genes may not only enable early disease detection but also determine the best treatments for individuals with certain cancers and other chronic and rare diseases.
The rise of artificial intelligence applications in life sciences companies, especially in research and development, is transforming the industry as earlier medical intervention and more sophisticated diagnosis and treatment can improve patient outcomes and extend human lifespan.
Jim Craig is Munich Re's senior vice president of North American underwriting and has worked in the life sciences liability underwriting field for more than 25 years. This year, he launched the company's life sciences liability division. Craig talks about how the application of artificial intelligence in life sciences is progressing and what factors companies need to consider to manage risks and best position themselves to take advantage of new opportunities.
Munich Re Specialty covers medical product liability and liability for financial losses caused by related errors and omissions. Areas of interest include branded and generic drug companies, over-the-counter and prescription drug manufacturers, clinical trial sponsors, dietary supplement manufacturers, medical device developers, contract service providers and animal health businesses.
In describing the life sciences liability landscape, Craig cited the transformative impact of artificial intelligence in underwriting life sciences organizations.
“Data is becoming an increasingly rich resource,” Craig noted. “Where this data is accessible, risk selection will become more accurate and sophisticated, while providing the opportunity to tailor insurance solutions to meet the complex challenges faced by life sciences organizations.”
For clinical trials, AI analysis of electronic medical record (EMR) records will continue to refine and speed up the recruitment and selection process of human trial subjects. Companies can pinpoint patient groups who are more likely to suffer from the disease the innovator is trying to cure. Biotech companies often struggle to meet subject recruitment targets across multiple trials. Craig noted that drug developers often seek coverage from insurance companies for upcoming trials. They estimate when clinical trials will begin and the number of participants. But they may only recruit half as many people as they need, causing them to over-insure the trial or extend coverage for the time it takes. Artificial intelligence can solve these problems by helping drugmakers make progress in quickly identifying the most suitable players.
Artificial intelligence can also be applied to the selection of therapeutic ingredients. Artificial intelligence algorithms can sift through vast amounts of scientific data, identify anti-cancer compounds and more, and predict how effective these chemicals will be in new drugs. AI algorithms can also analyze medical images more accurately than the human eye, Craig said. Artificial intelligence algorithms can analyze medical images with diagnostic accuracy comparable to expert radiologists.
Craig also shared several challenging areas of artificial intelligence:
- overdiagnosiswhich may cause unnecessary panic until the inaccurate diagnosis is corrected.
- unconscious discrimination This occurs when a clinical trial targets a specific population and a disease disproportionately affects certain groups. If AI systems steer companies toward specific groups without legitimate medical reasons, it could expose them to discriminatory behavior.
- Cybersecurity risks Aggregating and analyzing large amounts of medical data is of great significance. Companies need to protect large amounts of sensitive patient data that is attractive to cybercriminals.
Against the backdrop of the changing health technology landscape, where artificial intelligence is expected to play an ever-increasing role, Craig shares some tips for ensuring the right insurance coverage.
A lot depends on exposure to potential customers. Product liability insurance covers personal injury or property damage that may result when a company's products are tested in clinical trials or sold in the commercial market. Cyber liability to prevent cybersecurity incidents is another potential coverage.
“Errors and emissions liability comes into play when an organization performs work for others, and their negligence in doing the work could result in financial losses for their customers,” Craig said. “Errors and omissions liability insurance can respond to this. Relatedly, if their product has some kind of technical component. Technical E&O insurance can be important.”
If it is a complex product, such as a medical device where the insured may guide a doctor by phone or video during a procedure, then malpractice liability coverage will be very important in the event of product failure or practitioner malfunction.
Munich Re product aiSureTM Ensure protection against possible errors in AI models, such as hallucinations caused by generative AI, which can lead to lost revenue. It also covers errors that could result in business interruption, loss or legal problems for the insured. It may also cover other causes of loss.
“Illusion risk is a top concern for many of the clients we serve. Having adequate terms and conditions in a given insurance contract is very important to the clients we serve. These new AI clients are always exposed to regulatory risk,” Craig said.
In this growing industry with many players, Munich Re Specialty stands out in a few different ways. It has a dedicated life sciences liability underwriting division. The operator does not enter or exit the market. While the life sciences unit was launched this year, it is part of Munich Re Specialty's medical professional liability underwriting unit. It is committed to the long-term development of the sector and has a strong reputation and the financial strength to pay claims. Being part of a larger healthcare sector makes it easier for Craig to discuss policy development with his malpractice colleagues.
“It's great to have this collaboration under one umbrella. Another advantage is that we handle our own claims. We don't outsource it to a third party. If you don't know your claims, how can you know your book? By handling our own claims, that task is made easier,” added Craig.
The life sciences sector offers a wide range of opportunities for small and medium-sized companies to apply artificial intelligence to transform drug development and improve patient outcomes. Managing these risks and having the right insurance coverage is critical.
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photo: BlackJack3D, Getty Images
