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Home Financial Markets

Influence of VC on Healthcare R&D

Daily Remedy by Daily Remedy
August 2, 2021
in Financial Markets
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Vector files can be re-edit and used in any size

High resolution jpeg included. Vector files can be re-edit and used in any size

Convergence is a concept in evolutionary biology seen across many different ecosystems.

Different species converge to develop similar features and attributes when competing against one another in similar niches within a given ecosystem. This is why whales, which began as four-legged land mammals, developed fins and tails when they migrated into the ocean – and look very similar to the various fish populating the oceans.

The modern whale and fish occupy similar niches within the marine ecosystem, and consequently develop similar features.

But convergence also applies to business as well, and can explain many of the similarities we see across different industries. Fast food restaurants all operate under the same principles of streamlined labor and cost efficiencies – and often look quite similar barring a few tweaks in the branding and marketing.

It should come as no surprise then that convergence also applies to the economic models within healthcare, particularly the healthcare innovation niche. Traditionally healthcare adopts innovations derived through medical research, and once the research has proven successful or meaningful, we identify ways scale and apply it broadly.

When researchers first invented vaccines, it was developed in a lab and later scaled to healthcare systems across the country.

In this vein, research and development (R&D) is crucial to the healthcare economy. We develop new pharmaceuticals, devices, and therapeutics to improve the lives of patients suffering from medical diseases and ailments. As a result, life expectancy continues to grow (at least until the pandemic), and diseases that were once considered death sentences are now controlled with specific medications or treatments, allowing patients afflicted with those diseases to live normal lives.

However of late, a new player has entered the healthcare economy, one that plays a similar role to that of R&D – venture capital (VC). Like traditional R&D, VC pilots new innovations and identifies ways to scale those innovations.

But there are a few distinct differences. R&D does not have the same pressures to scale like VC, and the pipeline for funding is different.

R&D exists through a system of grants, largely controlled by federal government agencies, public entities whose mission is to fund the development of new science and technologies. VC exists through a system of private investors, albeit with some government funding, whose mission is to provide a return on investment.

The pressure to scale is greater with VC. And like all evolutionary processes, change is influenced by environmental pressures.

But like most evolutionary processes, success is not a zero sum game, though evolution always favors one species to be dominant. It is likely, given the broader trends in healthcare, that VC will assume the dominant role in the future of healthcare innovation, with important contributions coming from R&D, although at a much smaller scale.

Currently the annual federal budget for R&D is $52 billion, as per the National Institutes of Health, the largest and most prominent investment vehicle for R&D grants. In 2020, there was $21 billion invested into healthcare through various venture capital platforms, as per Mercom Capital Group.

In the coming years, this is set to change. We will see a growing influx of VC funds into healthcare, at the cost of R&D grants, until VC investments exceed traditional R&D funding mechanisms. A trend powered by healthcare’s heightened emphasis on scalability.

But the two will remain intertwined, coexisting in the same ecosystem of healthcare innovation, and influencing one another – although VC will have a greater influence on R&D, than the other way around.

VC models of investment have greater pressures to scale, and scale quickly. R&D funds focus more on the science, with scalability considered less important from the onset. However, this has changed. Now policy experts at the NIH and other federal agencies prioritize R&D projects that have a greater potential to scale – reflecting the growing influence of VC on healthcare.

An influence that will grow as healthcare is starting to favor such pressures of scalability.

Remember, animals evolve not relative to one another, but due to environmental pressures. And healthcare, still reeling from the lessons learned during the pandemic, is less focused on the latest, greatest technologies, and more on principles of health equity – providing the maximum clinical benefit to the maximum number of people.

That is code for scale.

This means the healthcare environment favors VC models – and healthcare innovation will acclimate accordingly.

VC will continue to grow in dominance, and R&D will focus on grants for projects that look more like startups tinkering with pilot models. Inevitably VC and R&D will begin to look similar, mirroring each other.

Like two animals competing in similar niches in the same ecosystem, with VC assuming the dominant position and R&D evolving to look like its more dominant competitor.

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Daily Remedy

Dr. Jay K Joshi serves as the editor-in-chief of Daily Remedy. He is a serial entrepreneur and sought after thought-leader for matters related to healthcare innovation and medical jurisprudence. He has published articles on a variety of healthcare topics in both peer-reviewed journals and trade publications. His legal writings include amicus curiae briefs prepared for prominent federal healthcare cases.

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In this episode, the host discusses the significance of large language models (LLMs) in healthcare, their applications, and the challenges they face. The conversation highlights the importance of simplicity in model design and the necessity of integrating patient feedback to enhance the effectiveness of LLMs in clinical settings.

Takeaways
LLMs are becoming integral in healthcare.
They can help determine costs and service options.
Hallucination in LLMs can lead to misinformation.
LLMs can produce inconsistent answers based on input.
Simplicity in LLMs is often more effective than complexity.
Patient behavior should guide LLM development.
Integrating patient feedback is crucial for accuracy.
Pre-training models with patient input enhances relevance.
Healthcare providers must understand LLM limitations.
The best LLMs will focus on patient-centered care.

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Large Language Models in Healthcare

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What the Most-Cited LLM-in-Medicine Papers Reveal—and What They Miss

What the Most-Cited LLM-in-Medicine Papers Reveal—and What They Miss

by Daily Remedy
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In just over two years, papers on large language models (LLMs) in medicine have accumulated nearly fifteen thousand citations, creating an academic canon that is already shaping funding decisions, regulatory conversations, and clinical experimentation. This study dissects the 100 most-cited LLM-in-medicine papers to show who is driving the field, which applications dominate attention, and where the evidence remains dangerously thin. What emerges is a picture of rapid intellectual consolidation—paired with a widening gap between technical promise and clinical reality. The...

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