Long before mRNA vaccines and biotech booms, drug hunting was inspired by the natural world. For close to 50,000 years, humans have used plants for medicinal purposes. That legacy lives on in aspirin, metformin, morphine, fingolimod, and countless other small molecule drugs.
This approach was successful but slow. Even in the twentieth century, scientists’ capacity to isolate and characterize biologically active chemicals in plants was just too limited and laborious. So, in the 1990s, the industry switched to a target-based approach, using combinatorial chemistry and high-throughput screening. Less structurally diverse synthetic libraries took center stage.
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Viswa Colluru Viswa is CEO of Enveda Biosciences. He founded Enveda after leading cross-functional teams across innovation, product strategy, and translational biology as an early employee at Recursion Pharmaceuticals. He holds a Ph.D. in immuno-oncology from the University of Wisconsin-Madison, where he developed new therapeutic agents for the treatment of prostate cancer. At Enveda, he […]
Three decades later, those barriers have been dismantled. Advances in microbial culturing, biosynthesis, analytical instruments, genomics, metabolomics, and machine learning have unlocked a brand new era in natural product drug discovery – one that is still ripe with potential. Only around 5% of plants have ever been studied for potential therapeutics and those that have are still largely a chemical mystery. On average, we do not know the chemical structures of 95% of the molecules within a plant. We’re just now tapping into this potential, with new tools that allow us to develop entire libraries of anthropological, chemical, and biological data from medicinal plants.
Plant Power
Natural products have a number of advantages when it comes to drug discovery. Unlike synthetic compounds, organisms such as fungi and plants are full of biologically active molecules that have evolved to interact, compete, and defend against other biological systems. Once isolated, they offer rich chemical and structural diversity. This successful translation to the clinic has meant that since 1981, more than 20 percent of newly approved drugs have been derived from or inspired by natural products. Oftentimes, their origins trace back to traditional medicine, which gave important clues around tolerability, efficacy, and safety.
While there is clear potential, scientists and companies in the 1990s also encountered many limitations. As new approaches to drug discovery emerged, they were quick to move on to greener pastures. Three shifts, in particular, catalyzed the movement away from natural products to synthetic libraries and high-throughput screening.
The first was the rise of combinatorial chemistry. This approach makes it possible to synthesize a vast array of compounds in a single process. Libraries of thousands or even millions of compounds can be developed and then screened using high-throughput automated assays. This gave pharma companies an unprecedented number of shots on goal.
A Deep-dive Into Specialty Pharma
A specialty drug is a class of prescription medications used to treat complex, chronic or rare medical conditions. Although this classification was originally intended to define the treatment of rare, also termed “orphan” diseases, affecting fewer than 200,000 people in the US, more recently, specialty drugs have emerged as the cornerstone of treatment for chronic and complex diseases such as cancer, autoimmune conditions, diabetes, hepatitis C, and HIV/AIDS.
A second factor was a growing belief that target-based drug discovery was superior. Prior to this, phenotypic screening was the norm. This involved testing a molecule in cells, isolated tissues, or perhaps mice to see what biological effect it had. Identifying the target and mechanism of action came later. With a target-first approach, scientists could screen vast synthetic compound libraries looking for candidates that bind a specific target of interest.
A separate but overlapping trend that fueled the migration was Big Pharma’s shift away from popular “low-hanging fruit” applications, such as the discovery of new antimicrobials. With their new priorities, the cumbersome process of culturing, purifying, and isolating novel bioactive compounds from natural products was just not worth the effort.
A New Era
Growing up in India, I learned to value and respect medicinal plants for their therapeutic properties. This is true of cultures around the world. What was missing was a repeatable system for identifying and isolating plant-based compounds at scale.
The return to natural product drug discovery has been driven by an all-star cast of scientific and technological advances – from genome mining to high-resolution mass spectrometry and molecular networking, which helps us visualize the rich analytical data we’re now able to generate. The rise of metabolomics allows us to simultaneously analyze multiple metabolites in a biological sample. These tools and advancements make identifying the mechanism of action and active molecules much easier.
This field is also particularly well suited to the application of machine learning. Natural product drug discovery slowed down in the 1990s in part because it was so laborious and difficult to scale. Thirty years later companies deciphering the underlying patterns with machine learning algorithms. Scientists are now answering questions we didn’t even know to ask three decades ago.
The field is also moving with unprecedented speed. Using a new set of algorithms, researchers were recently able to identify the specific antiviral molecules in E Dendroides, a Mediterranean shrub used for thousands of years for the treatment of warts. Within hours, a problem that had plagued researchers for over a decade was solved. By learning patterns of such bioactivity in molecules from thousands of plants, the same platform can identify what chemical modifications are needed to create patentable drug candidates.
Plant-based drug discovery may be tens of thousands of years old, but in 2021, it feels exciting, rich, and full of potential. Companies are rapidly building scalable databases with hundreds of thousands of unique chemicals and their links to biological signatures. Stepping back, the potential of natural product drug discovery is much broader. Other companies are combing the oceans in search of new marine sources (more than 28,500 marine natural products have been now identified). Small, biologically active venom peptides, known as conotoxins or conopeptides, have been isolated from snails. Even the human microbiome is being explored as a source for novel small molecule drugs. This new groundswell of activity hasn’t been achieved through just one technology. It’s the culmination of decades of advances, which now allow us to revisit the fertile drug hunting grounds of human history with unprecedented efficiency, scale, and scope.
Photo: LoveTheWind, Getty Images
Viswa is CEO of Enveda Biosciences. He founded Enveda after leading cross-functional teams across innovation, product strategy, and translational biology as an early employee at Recursion Pharmaceuticals. He holds a Ph.D. in immuno-oncology from the University of Wisconsin-Madison, where he developed new therapeutic agents for the treatment of prostate cancer. At Enveda, he leads a world-class team of machine learning scientists and drug hunters engaged in unlocking the potential of nature’s chemistry for drug discovery. By leveraging breakthroughs in computational metabolomics and machine learning, the Enveda platform works like a “chemical search engine” to predict new drug-like chemicals at scale. Enveda’s internal teams then advance these drug candidates through preclinical and clinical testing. With an initial focus on unraveling the chemical secrets of medicinal plants that have been used for thousands of years, Enveda’s first molecules are targeted towards cardiovascular, metabolic, and neurodegenerative conditions
