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Harvard Business Review
27-05-2025
- Health
- Harvard Business Review
AI Alone Won't Transform U.S. Healthcare
Imagine it's the middle of the night, and your child is seriously ill. You rush to the hospital, bracing for mountains of paperwork, long waits, and an overburdened staff. Instead, you meet a clinician who knows your child's medical history in precise detail. Within minutes, a specialist team evaluates your child and prescribes a personalized treatment plan tailored to her genetics and thousands of similar cases. No guesswork. No redundant testing. The diagnosis is clear, as is the path forward. Artificial intelligence could make this story the new normal. Not since the discovery of antibiotics has medicine faced such transformative potential. But AI alone will not deliver this future without serious structural reforms in the United States. We need to fix the flaws that have broken the current healthcare system. If we don't, AI could amplify the inefficiencies, misaligned incentives, and inequities that pervade healthcare today. With AI evolving at a blinding speed, the window to act is closing—along with the opportunity to ensure AI's benefits reach everyone. At Stanford, where I work, and across the industry, we are already seeing AI's real-world promise. Complex biological processes that once took scientists decades to describe are being illuminated by AI in a matter of months. AI is streamlining clinical trials, helping scientists identify new drug targets, and is even aiding in the development of novel therapeutics. The open question is whether these breakthroughs will translate into meaningful improvements in human health. Turning discoveries into better patient outcomes demands more than technological progress; it will require deep reforms in the U.S. healthcare infrastructure, payment systems, and clinical workflows. Without these changes, even the most promising innovations risk remaining stuck in research labs or limited to only those who can afford them. Avoid a Repeat of the EHR Experience The Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009, which mandated the adoption of electronic health records (EHR) systems, ushered in the digital age of medicine in the United States. But rather than improving the experience of care, for years, the transition saddled clinicians with overwhelming administrative burdens. Designed largely to satisfy insurers' complex billing requirements, EHRs often neglected the practical needs of doctors and patients. Even as EHRs have improved over time, they remain cumbersome, inefficient, and, in some cases, pose safety risks due to their user-unfriendly interfaces. Studies published in recent years have found that physicians spend a huge amount of their time on tasks related to EHRs, contributing to high burnout rates. We risk repeating this mistake with AI. Already, we see an AI arms race developing between physicians and insurance companies. Insurers are deploying AI tools to scrutinize and often rapidly deny treatment coverage, while physicians counter with AI-driven systems to justify necessary care. This technological tug-of-war doesn't improve care delivery; it merely shifts resources from patient care to battling within the system. To steer AI toward delivering a healthier future, we must pursue three urgent priorities: 1. Revamp incentives. The first step is to confront the incentives that shape healthcare today. Historically, market incentives have profoundly influenced the adoption of technologies, and not always for the greatest good. We must carefully design incentives to promote the outcomes we want and mitigate any adverse effects. AI cannot transform a system built on misaligned incentives. Today, fee-for-service reimbursement remains the dominant payment model in the United States, rewarding the volume of care delivered, not the quality or long-term impact of that care. This model prioritizes billing over clinical impact and continues to discourage interventions that emphasize prevention, early detection, and long-term health improvement. For instance, better management of early-stage diabetes could reduce all-cause mortality in patients by nearly 20%, yet reimbursement structures in the United States often fail to support the necessary long-term interventions. And across the board, tools that enable continuous monitoring, early diagnosis, or personalized treatment planning are often unfunded and underused. The Centers for Medicare and Medicaid Services (CMS) has been steadily advancing the shift toward value-based care —championing models that prioritize health outcomes over volume. While this represents an important step in the right direction, to realize the full potential of these reforms, we must ensure that AI is embedded in the next generation of value-based care strategies. That includes updating billing codes to reflect AI-enabled procedures, expanding coverage for digital diagnostics and remote monitoring tools, and creating reimbursement pathways that reward the use of AI in preventing disease, not just treating it. Legislation like the recently introduced bipartisan Health Tech Investment Act offers a timely and promising framework. The bill proposes expanding reimbursement pathways for digital health technologies, including AI, and enabling their adoption across diverse clinical settings. Structured financial support like this is critical to avoiding a fragmented future where only well-resourced institutions have a role in shaping AI-supported care. AI can also be part of the solution to reimbursement challenges, but it must be approached thoughtfully. By carefully deploying AI to automate processes like eligibility verification, claim submissions, and real-time error detection, we can reduce administrative burdens without exacerbating the tug-of-war between payers and providers. Done well, this could free up time and resources to focus on what matters most: the patient. 2. Embed AI into medical education and training. EHRs fundamentally changed the way healthcare providers work, often in ways that weren't fully anticipated or understood. Studies on EHR rollouts highlighted significant workflow disruptions, unsafe workarounds, and documentation errors, often due to gaps in training and understanding. AI will bring equally profound changes, creating a significant training challenge and cultural shift. In medicine, we contend with a significant 'know-do gap': the lag between when we know something is beneficial and when it is actually adopted in practice. On average, it takes 17 years for new evidence-based practices to become the standard practice in the United States, largely because of a stubborn commitment to entrenched practices and the daunting volume of emerging data that healthcare providers must interpret. Overcoming these barriers requires continuous education and systemic changes to encourage rapid integration and adaptation of new knowledge. Integrating AI into medical education curricula is a critical part of the solution. Future generations of providers must be educated and equipped with the skills and mindset necessary to integrate AI into patient care. Beyond the classroom, health systems must also expand training opportunities and foster a culture of continuous learning to ensure that their healthcare professionals are ready to embrace AI as a tool to enhance what they do best. The opportunities are, indeed, significant. Consider the use of AI-supported tumor boards, which could revolutionize oncology care. Tumor boards are specialized, multidisciplinary teams of healthcare professionals who meet to discuss cancer cases and determine the best treatment plans for patients. AI could enhance how tumor boards assimilate the latest research, patient data, and expert insights, helping close the know-do gap in implementing new cancer treatments. With research grant support, Stanford Medicine is actively exploring this type of AI integration. 3. Engage doctors and patients in AI development and use. Because the development of EHRs largely excluded the voices of doctors and patients, the tools didn't meet their needs. Recent surveys show that 50% of physicians feel EHRs have compromised their clinical effectiveness, and nearly 60% advocate for a complete overhaul of these systems. For AI to avoid this pitfall, physicians and patients must be actively involved in the development, testing, and implementation of AI tools from the beginning. According to an American Medical Association (AMA) survey, 7 8 % of physicians want clear explanations of how AI systems make decisions. Yet, many systems still lack the transparency needed for clinicians to understand and trust AI-generated recommendations—a challenge we cannot afford to overlook. If patients are to trust AI, they, too, need to be engaged. Already, there is concerning evidence of patients growing skeptical of AI. A 2023 Pew Research Center study found that 60% of Americans would feel uncomfortable if their healthcare provider relied on AI for diagnosis and treatment recommendations. To mitigate these risks, AI tools must be developed using diverse data sets that represent a broad range of populations. In addition, involving patients and clinicians in the design and testing phases will ensure that AI tools are equitable, trustworthy, and effective across different demographic groups. In fact, it's the human factor—equipping patients and physicians to use AI to make better care decisions—that will allow for a smoother integration of these tools. As AI systems become more advanced, a critical question is how they should be used in clinical decision-making: as tools to assist physicians or as autonomous agents making decisions independently. At Stanford, we share the view with many others that in the near term AI should be used to support, not replace, clinical judgment. Over time, however, as AI models become more capable and are validated in real-world settings, the line between support and autonomy may blur. This evolution underscores the importance of rigorous, ongoing oversight and regulation. Regulatory frameworks, such as the Food and Drug Administration's approach to monitoring continuously learning algorithms, will need to keep pace with technological change while ensuring safety, transparency, and equity. AI represents a rare opportunity to transform the future of healthcare. But this transformation will not happen automatically. We must act deliberately and learn from past mistakes. By aligning incentives, fostering a culture of continuous learning, and involving all stakeholders, we can ensure that AI delivers a better healthcare system in the United States—one that works for everyone.
Forbes
27-05-2025
- Business
- Forbes
Tying U.S. Drug Prices To Foreign Markets Risks Innovation And Lives
"The higher prices that Americans pay for drugs cover a disproportionate share of the research and ... More development efforts from which the entire world benefits," writes health policy expert Sally C. Pipes. Earlier this month, President Donald Trump signed what he called 'one of the most consequential Executive Orders in our Country's history.' The order is essentially an updated version of his administration's 2020 'Most Favored Nation' policy. It directs pharmaceutical companies to tie the U.S. prices of their drugs to the lower prices that other developed countries pay. It certainly seems unfair that Americans pay more for drugs than foreigners. So the president's insistence that drug companies offer Americans the best deal they provide worldwide has intuitive appeal. But the economics behind this proposition are much more complicated. The higher prices that Americans pay for drugs cover a disproportionate share of the research and development efforts from which the entire world benefits. Like it or not, we have become the world's medicine chest. Pegging drug prices here to those in other countries would yield minimal savings for the United States and devastate funding for biomedical research. In the long run, pharmaceutical companies would develop fewer novel lifesaving drugs. And that would consign Americans and foreigners alike to undue suffering. Other countries pay less for pharmaceuticals because their governments forcibly cap prices. If drug companies want to sell their wares within that country's borders, they have to assent to the foreign government's price. That strategy has trade-offs. For starters, manufacturers prioritize markets where they can garner higher returns. So they tend to delay launching their drugs in countries with price controls. Across the G20 group of middle- and upper-income nations, just 38% of new medicines launched between 2012 and 2021 were available as of October 2022. In the United States, 85% of those novel drugs were available. Even in our peer countries, foreign patients lack access. Just 61% of those drugs were available in Germany, 59% in the United Kingdom, 45% in Canada, and 34% in Australia. One study found that European countries with their own versions of 'most favored nation' policies experience delays of up to one year for new drugs. Such launch delays reduce life expectancy for patients in these countries. Drug companies prioritize markets where they can charge higher prices—like the United States—because drug development is risky and expensive. It takes about $2.6 billion and more than a decade, on average, to bring a single new drug to market. And roughly 90% of drug candidates fail to gain approval. The attractiveness of the U.S. market to drug makers has also resulted in significant benefits for our economy. Currently, two out of three new drugs are developed in the United States. Where will that drug research go if the United States imports foreign price controls with a 'most favored nation' policy? It will likely go to China—if it does not disappear entirely. Already, the outlook for drug research in the United States is growing bleaker. The price controls established in Medicare by the Democrats' 2022 Inflation Reduction Act are projected to result in the development of 139 fewer drugs by 2035. That could include cures for rare cancers or Alzheimer's. But even if the drugs that go undeveloped would simply offer moderate improvements on chronic diseases, sacrificing them is still too high a price to pay for potential short-term price reductions. And about those 'reductions.' Should the Trump administration successfully implement a most favored nation policy, drug companies are likely to respond by raising prices in other countries—or pulling them from the market there altogether. According to a 2022 study by researchers from UCLA, Stanford, and France's University of Toulouse Capitole, 'reference pricing induces a substantial increase in the prices charged in reference countries but only a modest decrease in the prices charged in the US.' Poorer countries are ill-equipped to handle higher prices. So Americans may save figurative pennies—while foreigners lose access to lifesaving drugs entirely. There are better ways to lower drug prices in the United States. Pharmacy benefit managers and other middlemen claim roughly half of every dollar spent on prescription drugs in this country. Congress and the administration can rein in their market-manipulating abuses that drive up prices for consumers. The administration can also insist that other countries pay prices commensurate with the value of new medicines as a condition of striking trade agreements with the United States. Doing so would help ensure that foreign countries pick up a bigger share of the globe's research and development tab. The laws of economics are stubborn things. If the Trump administration really wants to do the most good for patients in the United States and worldwide, they'll scrap this most favored nation order.
Associated Press
21-05-2025
- Business
- Associated Press
SynVivo Appoints Dr. Richard Eglen to Board of Directors
HUNTSVILLE, Ala., May 21, 2025 (GLOBE NEWSWIRE) -- SynVivo, a pioneering organ-on-chip company developing advanced microfluidic platforms that replicate human tissue microenvironments for drug discovery, today announced the appointment of Dr. Richard Eglen as a non-executive member of its Board of Directors. Dr. Eglen brings over 40 years of leadership experience in the life sciences industry, having held senior roles at Corning, PerkinElmer (now Revvity), DiscoverX (now Eurofins), and Roche. Most recently, he served as a senior advisor to Arsenal Capital Partners and currently sits on the boards of several prominent life science organizations. SynVivo's mission is to revolutionize biomedical research and therapeutic development by providing predictive in vitro models that recreate complex human tissue biology with exceptional accuracy. This mission aligns closely with the FDA's recent Modernization Act and updated guidance encouraging the use of innovative, human-relevant technologies to improve drug safety and efficacy assessments. 'We are excited to welcome Dr. Eglen to SynVivo's Board,' said Gwen Fewell, PhD, President and CEO of SynVivo. 'His vast experience and insight will strengthen our leadership team as we scale our offerings to address critical gaps in drug development with more predictive and human-relevant platforms.' 'I am delighted to join SynVivo at this pivotal time,' said Dr. Eglen. 'I look forward to supporting the company's mission to advance innovative technologies that improve drug discovery outcomes and align with regulatory priorities aimed at modernizing preclinical testing.' Dr. Eglen's appointment reinforces SynVivo's commitment to advancing organ-on-chip technology as a transformative tool for drug discovery and translational research. His expertise will support the company's growing efforts to deliver scalable, reproducible solutions for biotech, pharma, and academic partners worldwide. About SynVivo SynVivo is a pioneering organ-on-chip company developing physiologically relevant tissue models for drug discovery, disease research, and safety testing. Its advanced microfluidic platforms replicate human tissue microenvironments to enhance the predictive accuracy of in vitro testing. SynVivo is committed to bridging the gap between traditional preclinical models and human clinical outcomes, advancing a new standard in predictive, human-relevant drug development. Media Contact: Gwen Fewell, PhD President & CEO [email protected] A photo accompanying this announcement is available at
