Bringing a new medicine to market routinely costs more than $1 billion and can take over a decade to complete. Many of the delays driving those costs stem from operational bottlenecks, fragmented data systems, enrollment challenges, and poor visibility across increasingly complex development programs. As pharmaceutical companies race to develop therapies for obesity, diabetes, and other high-cost chronic diseases, competitive advantage is increasingly determined by execution.
Medical professionals like Dr. Thao T. Pham, PharmD, focus on addressing the inefficiencies that slow clinical development, increase costs, and delay patient access to new therapies, one of the industry’s most expensive problems.
Clinical trials require coordination across regulatory teams, manufacturers, clinical operations groups, safety organizations, supply chain partners, commercial stakeholders, and investigators spread across multiple regions. As programs become larger and more global, information often becomes fragmented across departments, creating blind spots that can evolve into costly delays.
“The clinical trial system is genuinely one of the most complex and resource-intensive processes in all of medicine,” Dr. Pham said. “Collectively, these factors contribute to a development cycle that averages over a decade and costs well over a billion dollars per approved medicine, and they ultimately delay patient access to therapies that are already showing promise.”
Every month a therapy remains in development consumes valuable patent life while generating no revenue. For blockbuster therapies in competitive markets, a one-year delay can translate into hundreds of millions of dollars in lost commercial opportunity. And this is changing how pharmaceutical companies think about trial execution.
Historically viewed as a support function, clinical operations are increasingly becoming a way for companies to identify risks earlier, maintain enrollment timelines, and coordinate globally distributed teams more effectively. They are attempting to move therapies through development faster than competitors pursuing similar scientific approaches.
Dr. Pham has focused on developing integrated timelines, centralized reporting systems, and cross-functional coordination structures that improve visibility across large development programs. The aim is to reduce uncertainty before it becomes expensive.
“The most immediate impact is on risk visibility,” Dr. Pham said. “A big part of my role was building integrated timelines and centralized reporting specifically so that dependencies and risks were visible before they became delays.”
The industry has also shifted focus to representation in clinical research. Many trials fail to adequately reflect the populations that will ultimately use approved therapies. Regulators, healthcare systems, and payers are paying closer attention to whether clinical data reflects real-world patient populations.
Dr. Pham’s findings identified persistent underrepresentation among populations disproportionately affected by obesity, highlighting how enrollment strategies can influence both scientific validity and downstream adoption.
“The most immediate risk is regulatory,” Pham said. “FDA has been increasingly explicit about expecting diverse trial populations, and companies that submit data packages built on narrow, non-representative samples are facing harder label negotiations and in some cases, requests for additional post-marketing studies.”
These operational challenges are also creating opportunities for technology companies. Patient recruitment remains heavily manual, and clinical data often live across disconnected systems. Project management workflows still rely on fragmented tools that make it difficult to track risks, budgets, and timelines in a unified way.
As artificial intelligence, decentralized trials, and real-world data become more widely adopted, the next major advances in drug development may come as much from infrastructure innovation as scientific discovery. Companies that successfully modernize clinical operations stand to reduce costs and improve development productivity across entire portfolios.
For an industry that spends hundreds of billions of dollars each year pursuing new therapies, even modest gains in efficiency can generate outsized returns. Through her work improving clinical trial execution, strengthening data visibility, and advancing conversations around more representative research, Dr. Pham is contributing to a needed transformation in how pharmaceutical companies develop and evaluate new treatments.
“The economic impact across all of these is not incremental,” Pham said. “Faster decisions, lower per-trial costs, and higher success rates compound over a portfolio, and for an industry spending hundreds of billions on development annually, even modest efficiency gains at scale translate to enormous savings and earlier patient access.”
