Shipping Up to Boston: Takeaways from Healthtech Leaders@LSX World Congress USA
A few of Taazaa’s leaders shipped up to Boston in early September, but it wasn’t to find a wooden leg.
They were there to meet with other healthtech leaders at the LSX World Congress USA, a gathering of the top companies from the US biotech, medtech, and healthtech sectors—including Taazaa, one of this year’s sponsors.
The conference’s purpose was to help early- and growth-stage healthtech and digital health innovators connect with the capital, partners, and expertise they need to grow their companies, develop their products, and deliver them to a global market.
CEO Yasir Drabu and Chief Growth Officer Trip Bodley accompanied Taazaa’s Client Partner, Darren Phelps, to showcase our innovative healthcare solutions and explore new partnership opportunities.
The trio engaged in discussions and collaborative sessions about current trends shaping the future of healthcare technology. We asked them to tell us some of their takeaways.
AI Is Fueling Innovation
“There’s a lot of innovation happening in life sciences,” Yasir said. “AI is playing an important role in how they’re bringing new drugs to the market faster.”
For example, AI algorithms analyze vast datasets to identify potential drug candidates more quickly and accurately than humans can. Machine learning models can predict how different compounds will interact with targets, significantly speeding up the discovery process and reducing costs. AI also helps design more effective clinical trials by predicting which patients will likely benefit from specific treatments.
AI is also helping to identify new uses for existing drugs by analyzing vast amounts of biomedical data. This approach can significantly shorten the time needed to bring a new treatment to market.
Personalized medicine is another innovation attendees were talking about at LSX. AI enables more precise personalization of treatments by analyzing genetic, environmental, and lifestyle data. Pharma leaders are starting to create more effective, tailored therapies for individual patients. AI-driven analysis of genetic data can help identify biomarkers for disease and predict responses to different treatments.
“One way AI is speeding up time to market is by improving the design and execution of clinical trials,” Yasir said. AI can better identify suitable candidates, predict potential adverse effects, and optimize trial protocols, which means more efficient trials and faster approvals.
AI solutions are also helping relieve the burden on overwhelmed healthcare staff, which in turn is improving the quality of care. Even surgeons are getting help from AI-powered instruments and surgical robots.
The Biotech and Therapeutic Market Is Down
“Currently, the market condition for biotech and therapeutic companies is not great,” Yasir said. “The investors and the ecosystem are saying, be careful with your cash. Think carefully about how you deploy it. The valuations are not there; the money is not there.”
While the biotech and therapeutic sectors show signs of bouncing back, there’s been a decrease in investments from nearly 30 billion pre-COVID down to nine billion currently.
Additionally, investors are shifting and being more selective. The size of private funding rounds may be increasing overall, but funding has decreased for preclinical. Investors are increasingly focused on companies with advanced clinical trials or those addressing high unmet medical needs.
Healthtech Regulations Are Changing
Regulatory agencies are racing to catch up to technology innovations—particularly AI.
With the rise of technologies like artificial intelligence, machine learning, and advanced data analytics in healthcare, regulators are adapting their frameworks to address new types of products and services. This includes updating guidelines for software as a medical device (SaMD), digital therapeutics, and telemedicine.
Many regulatory bodies are working to streamline approval processes to bring innovative health technologies to market more quickly. For example, the FDA has introduced programs like the Breakthrough Devices Program and the Digital Health Innovation Action Plan to expedite the review of certain healthtech products.
Another factor impacting the regulatory space is international harmonization. There is a growing trend toward harmonizing regulations across different countries to facilitate global market entry for healthtech products. Organizations like the International Medical Device Regulators Forum (IMDRF) are working to create more consistent regulatory standards worldwide.
“Judging by the conversations I was involved in,” Yasir said, “the feeling seems to be that the regulatory landscape is becoming more dynamic and adaptable to rapid advancements in health technology, which is good news. But it underscores the importance of working with a technology partner who keeps up with regulatory changes and can pivot quickly if a change impacts product development.”
Data Quality and Security Remain a Focus
Data protection remains a critical focus, particularly as emerging regulations place greater emphasis on the secure handling of health data and patient consent. And in the new age of AI, the importance of data quality is rising.
“I noticed a lot of interest in approaches to data security, approaches to interoperability,” Darren said. “How do healthtech, medtech, and digital health businesses work within their partner ecosystems to maintain data security but still allow a network of third-party collaborators secure access to that information in line with protocols like HL7 FHIR? Data interoperability, security across those protocols, that was certainly a prominent theme.”
Data quality and its readiness for consumption by AI tools was another popular topic. “I kept hearing people talking about the quality of data,” said Trip. “It’s junk in, junk out. If you have bad data, you’re going to get bad outcomes from your AI models.”
The “garbage in, garbage out” (GIGO) concept is nothing new, but in the AI era, it’s become critical—especially in healthcare. AI models, including machine learning and deep learning models, rely heavily on quality data for training and validation. An AI model will generate unreliable or just plain wrong results if the training data is biased, incomplete, or contains errors.
Organizations seek healthtech partners they can trust to keep their data secure and ensure that it’s clean, deduplicated, and of the highest quality.
Trust Is Key for Healthtech Partners
“Most organizations seeking healthtech partners won’t, by default, trust that partner at the outset,” Yasir said. “One of the attendees told me, ‘We as an organization don’t trust anybody. We’ve had data breaches in the past, or something has gone wrong. We don’t want to get hit with that again.’ So they’re coming from a place of zero trust.”
Darren agreed. “It was extremely prominent in the conversations we had, and it goes beyond just the healthcare or healthtech space. Every business in every industry grapples with data security and whether or not they can trust their tech partners.”
“Trust is key. That’s one of the most gratifying things about what we do,” Trip added. “When someone partners with us, that’s meaningful. That’s a bond of trust.”
Did we miss you?
Were you at LSX and didn’t get a chance to talk to us? Give us a buzz! We’d love to discuss what you’re looking for in a healthtech partner.
