Precision Medicine Strategies
In the clinic, precision medicine aims to select the best therapies for each patient based on factors like genetics, metabolic profile, lifestyle, comorbidities, and environment. But even in preclinical drug discovery, the quest for precision medicine is making its mark.
Companies and academic labs are designing drugs for specific subsets of patients based on their genetic profiles or to specifically target their tumors' mutations. This precision is important in oncology because of the high heterogeneity of many tumor types, both within one patient and between patients who have the same type of cancer, such as melanoma or breast cancer.
For example, the tumor-agnostic drugs larotrectinib and entrectinib were designed to target the NTRK fusion protein, which drives growth in a subset of tumors, regardless of the organ from which the tumor originated. The FDA granted approval to these drugs in 2018 and 2019, respectively, and approved diagnostic tests meant to identify patients with the NTRK fusion protein who can benefit from these drugs.
Clinicians, corporate and academic researchers, and regulators are working together to overcome challenges and pave the way for more therapies that can contribute to precision medicine.
AI in Drug Discovery
AI systems are becoming more prevalent in multiple stages of drug development. Drug developers are using AI systems to identify promising drug targets, predict the bioactivity and toxicity of new molecules, plan syntheses of novel compounds, design and prioritize drug leads, and look for potential ways to repurpose existing drugs. Keeping abreast of these innovations is essential in today's drug development world.
AI tools are helping scientists predict protein structures and understand how drug candidates might bind to a protein of interest. Machine learning and physics-based computational drug design are being used to digitally screen billions of compounds.
Other AI platforms aim to help drug developers identify safety concerns and focus their laboratory and clinical trial efforts on the compounds most likely to succeed. For example, a research team in China developed a platform that uses deep neural networks to help drug developers predict which of their lead compounds is likely to have off-target effects on any of 391 kinases.
Delivering More Predictive Outcomes with 3D Cell Cultures
Meanwhile, researchers are increasingly turning to 3D cell cultures to get a more physiologically relevant view of drug candidates' potential for success. Compared to 2D cell cultures, 3D cultures such as spheroids and organoids can better mimic the in vivo environment of cells within an organ or a tumor. This allows 3D cultures to capture aspects of the in vivo environment, such as concentration gradients for drugs, oxygen, and metabolites; cell-cell and cell-extracellular matrix (ECM) interactions; and heterogeneity within an organ or tumor — any of which can affect how drugs will function within the bodies of real patients.
In line with the recent legislation that eliminates requirements for preclinical animal testing, the FDA has signaled its support for gradually reducing the use of animal models through the development of alternative techniques such as organ-on-a-chip methods. These changes highlight the importance of and opportunities in developing robust 3D culture models that capture important aspects of human biology while avoiding the effects of inter-species differences.
In preclinical drug development, 3D culture is enabling researchers to move toward precision medicine and future therapies. In oncology, 3D cultures give researchers the opportunity to better replicate the complexity of real tumors, such as by culturing organoids that contain multiple cell types to mimic tumors that contain multiple cell types or multiple mutations in vivo. Exciting technological developments are enabling the miniaturization of 3D cultures, including scaffold-supported organoids, so they can be used in high throughput applications.
The increasing ease of using 3D culture systems also gives scientists who wish to perform more realistic assays the ability to scale up patient-derived cells to the large volumes needed for drug screening or molecular studies rather than waiting for rarely available clinical samples. In combination with miniaturization techniques, this allows researchers to screen libraries with hundreds of thousands of compounds directly against 3D spheroids derived from patient cells.
Being Part of the Future
Trends like precision medicine, AI in drug development, and 3D cultures are opening new possibilities for research directions, including ways of using these strategies in combination. One example is research programs that match cancer patients to the most effective drugs by growing patient-derived tumor cells or tumoroids, which allows researchers to screen approved drugs for effectiveness against the patient's own tumor cells.
Life sciences manufacturers and scientists must collaborate to keep these exciting trends moving forward. Because technologies like organoids are dependent on complex inputs to use them in a scalable way, drug development labs are collaborating with companies that have expertise in setting up 3D culture systems to solve problems as they arise. In turn, manufacturers can collect feedback from corporate and academic researchers on what problems they're trying to solve to design products accordingly.
Corning Life Sciences offers a wide variety of tools and expert support to help you solve drug development challenges. With more than 35 years as a leader and innovator in 3D cell culture, we offer gold standard ECMs like Corning® Matrigel® matrix, permeable supports, and 3D culture flasks and microplates, along with a full line of products and tools for drug discovery.
Stay informed with Corning's extensive library of protocols, webinars, and articles to stay abreast of the latest drug screening and 3D culture tools and trends. Learn more about 3D Cell Culture and Drug Discovery Solutions.
