The Economics of Drug Discovery: Why Faster Preclinical Testing Saves Millions
CellField Technologies • February 12, 2025
The High Cost of Drug Development
Bringing a new drug to market is an expensive and time-consuming process. On average, it takes 10-15 years and costs upwards of $2.6 billion to develop a single FDA-approved therapy. A significant portion of this expense comes from preclinical testing, where pharmaceutical companies determine whether a new compound is safe and effective enough to enter human trials. Every delay at this stage compounds costs, resulting in lost revenue opportunities and extended market entry timelines.
Where Preclinical Delays Hurt the Most
Traditional preclinical models, particularly animal testing, have inherent inefficiencies that contribute to delays and high failure rates. Key issues include:
- Poor Predictive Accuracy: Animal models often fail to replicate human biological responses, leading to wasted investment in non-viable drug candidates.
- Regulatory Hurdles: Navigating preclinical regulatory requirements can be slow and costly, especially if additional studies are required.
- Operational Inefficiencies: Standardized preclinical testing processes involve extensive lab work, resource allocation, and personnel time, all of which drive up costs.
The Business Case for Faster Preclinical Testing
To mitigate these financial risks, biotech companies are turning to more predictive, scalable, and cost-effective solutions like organ-on-a-chip models and advanced in vitro systems. These innovative technologies offer:
- Faster Data Collection: Microphysiological systems (MPS) provide real-time insights into drug interactions, cutting months off testing timelines.
- Reduced Failure Rates: By more accurately mimicking human joint tissues, platforms reduce the likelihood of investing in non-viable candidates.
- Lower Cost per Test: Unlike expensive animal studies, in vitro models allow for scalable and repeatable testing at a fraction of the price.
Financial Impact: How Efficiency Translates to Market Advantage
Pharmaceutical companies operate in a competitive landscape where time-to-market can determine a drug’s commercial success. Every day of delay in drug development costs an estimated $500,000 in lost revenue and $40,000 in direct clinical trial costs. By adopting faster, more reliable preclinical methods, companies can:
- Bring therapies to market faster, leading to earlier revenue generation.
- Reduce R&D expenses, making investment dollars more efficient.
- Improve investor confidence, leading to stronger funding opportunities and market positioning.
The shift toward efficient, human-relevant preclinical testing isn’t just a scientific breakthrough—it’s a financial imperative. Companies that leverage advanced models stand to gain a significant competitive advantage in the race to bring innovative joint disease therapies to patients.
Biotech News
Intern Spotlight: Heath Fellows Heath is from Lake Tahoe, California, and currently studies at Bates College, where he’s majoring in Biochemistry with a minor in Computer Science. His passion for biotechnology stems from a deep fascination with how the field merges science and innovation. Originally entering college thinking he would pursue medicine, Heath quickly found himself drawn to biotech after taking several organic chemistry courses. His interest in computer science, which began in high school, led him to envision a future where he could combine both fields ideally in biostatistics or another area that merges computation with biology. Heath’s introduction to research began early, during high school. For his senior thesis, he designed an original project focused on post COVID facial recognition, specifically how masks affected recognition accuracy. He built and coded facial recognition trials himself and conducted the study using middle school students as participants. The experience taught him how to frame research questions and build a project from the ground up, and it sparked his love for building things whether in code, design, or science. When asked why he wanted to intern at CellField Technologies, Heath said the company’s mission really stood out to him. He saw firsthand how joint diseases like osteoarthritis impact people close to him, and the opportunity to work on research aimed at prevention and better diagnostics felt meaningful. He also appreciated CellField’s ethical commitment to reducing animal testing, something he strongly supports. After researching the company, Heath was particularly fascinated by the MAJIC system and knew he wanted to contribute to the team’s work. Since day one, Heath has been hands on. He began his internship designing a 3D model of one of the company’s chips, starting from blueprint history files. While it may seem straightforward, the modeling required extreme precision and every angle and measurement needed to be just right. He’s spent time learning the 3D printer workflow and mastering new software to help modify components of the chips. Looking ahead, his work will expand into cell culture, where he’ll help grow donor derived joint cells on the chip. Heath has already learned a tremendous amount in his time with CellField from advanced lab tools and techniques to foundational knowledge about osteoarthritis and the materials used in tissue engineering. He attends monthly meetings with Poly Med, where he’s exposed to cutting edge biomaterials and ideas. He speaks highly of Dr. Wood, praising his ability to explain complex topics clearly and concisely. Looking to the future, Heath sees this internship as a powerful stepping stone. Heath says the skills he’s learning from 3D modeling to cell culture and electrospinning will serve him well as he moves forward in biotech. He's also excited about the connections he's making in New England and enjoys working in Portland. Outside of the lab, Heath is an avid cyclist. He bikes to work every day logging a total of 58 miles daily and races competitively as part of a Portland based team. He also enjoys painting, art, and spending time with friends in the city. In three words, Heath describes his experience at CellField Technologies as: innovative, challenging, and eye opening. And his dream vacation? Anywhere in Italy, especially Lake Como. He loves the food, fashion, and culture, and hopes to explore the countryside and visit Italy’s iconic cities one day.
I ntern Spotlight: Tommy McGuire Tommy McGuire is a senior at the University of New England studying Business Administration. Originally from New Jersey, Tommy brings a strong interest in how businesses operate and grow. This is something he developed early on with one of his first jobs selling PPE products. He joined CellField Technologies in January after finding the opportunity on Handshake. At the time, he wasn’t familiar with biotech or joint-on-a-chip platforms, but was interested in stepping into something new. Since then, he’s been drawn in by the mission and the impact CellField is working to help in drug research for treatment of joint disease. At CellField, Tommy creates articles for the company’s LinkedIn and website, helps manage the content schedule, and is soon to take on accounting responsibilities. He also led the team’s pitch for the Top Gun competition in May, gaining valuable experience in business strategy and presentation. He says the internship has helped him grow professionally, build strong connections, and gain a better understanding of the kind of work he wants to pursue after graduation. Outside of work, Tommy enjoys fishing, golfing, working on cars, and spending time with friends and family. He’s always looking for adventure, especially near the beach. His dream trip is to Italy, especially San Donato where his mothers family is from. This is a place he hopes to visit to connect with his roots and experience the culture. When asked to sum up his time at CellField so far, Tommy says it’s been a valuable experience full of learning, growth, and new opportunities.
June 10, 2025 CellField Technologies The National Institutes of Health (NIH) recently announced a shift in its approach to biomedical research, signaling an intention to reduce the use of animals in NIH-funded studies. This decision, influenced by both scientific and ethical considerations, represents a major inflection point in how preclinical research is conducted in the United States. For decades, mice, dogs, and non-human primates have served as the backbone of early-stage drug development. However, their predictive power has come under increased scrutiny. The FDA has reported that over 90 percent of drugs that succeed in animal testing ultimately fail in human clinical trials. These limitations, combined with mounting public pressure and new regulatory frameworks, are driving a transition toward more human-relevant alternatives. A Turning Point in Preclinical Research The NIH’s new policy reflects a broader consensus that animal models often fall short in replicating human disease biology. Differences in immune systems, metabolic pathways, and tissue responses mean results from animal studies don’t always translate effectively to people. In response, researchers and companies are exploring technologies that model human physiology more directly. The FDA’s 2022 Modernization Act reinforced this direction by allowing the use of non-animal technologies, including organ-on-a-chip systems, microphysiological models, and computational approaches, as part of the regulatory review process. The NIH is now aligning its funding priorities with these developments. This convergence of policy, public sentiment, and scientific progress is opening the door for a new generation of tools designed to improve both ethical standards and scientific accuracy. New Tools for Human-Relevant Insights As the research community looks for alternatives to animal testing, several platforms have emerged that aim to replicate human disease processes more faithfully. Among these, microphysiological systems that model specific tissue environments are becoming increasingly important. For joint diseases like osteoarthritis and rheumatoid arthritis, new platforms are offering insights into tissue degeneration, inflammation, and treatment response without relying on animal data. One such model, for example, integrates primary human joint cells into a microfluidic environment that mimics the physical and biochemical conditions found in actual human joints. This approach allows researchers to monitor live-cell activity, analyze real-time biomarker changes, and study therapeutic effects with greater precision than animal models typically allow. These systems are not just ethically sound. They are designed to improve research outcomes by making early-stage drug testing more relevant to human biology. A Shift That Requires Collaboration Although NIH’s policy does not eliminate animal research altogether, it makes clear that future grant proposals will need to justify animal use more rigorously. Validated non-animal models are no longer optional; they are expected wherever possible. The private sector has an important role to play in this transition. Companies developing robust, reproducible, and disease-specific models are helping move the field toward a more reliable and humane research infrastructure. When these tools are developed in collaboration with academic partners and aligned with regulatory expectations, they don’t just replace animal models, they redefine what effective preclinical research can look like. Looking Ahead The shift away from animal testing is part of a larger transformation in the life sciences, one that favors specificity, reproducibility, and translational relevance. As the NIH reorients its funding strategy and the FDA continues to embrace non-animal data, researchers will need to adopt tools that are built for this new era.
