As part of WuXi AppTec’s ongoing efforts to collaboratively foster new thinking and actionable approaches in advancing breakthroughs for patients, we have launched a new interview series in 2022 – “Delivering on the Promise of New Modalities” – so leading voices of R&D can share how their approaches are addressing the barriers standing in the way of breakthroughs.
For our next interview as part of our featured series highlighting innovation in our ecosystem, we sat down with Maria Luisa Pineda, CEO and Co-founder, Envisagenics. As a spinout of the world-renowned Cold Spring Harbor Laboratory (CSHL) and an artificial intelligence-driven biotechnology company, Envisagenics focuses on diseases that are driven by splicing deregulation. With this scientific premise, Envisagenics primarily focuses on three therapeutic areas – oncology, neurodegenerative, and metabolic disorders. The company secured Series A financing in 2021 to continue to develop and improve its machine learning based drug discovery SpliceCore® platform and to discover and develop novel RNA splicing therapeutics. In November 2022, Envisagenics announced a multi-year research collaboration agreement with Bristol Myers Squibb for accelerated discovery and development of oncology therapeutic candidates.
Greetings Maria, nice to have you today. Could you please introduce Envisagenics’ platform to our readers? What is the top industry-wide challenge your company tries to solve?
Maria: As an AI-driven biotech company, we maximize the power and potential of sequencing data for the discovery of targets for therapeutic development. Traditional drug discovery paths are long, expensive, and often fail to reach patients. Envisagenics is capitalizing on the value of RNA sequencing data to identify novel RNA splicing derived targets in-silico and understand the mechanism of action for each target prior to validating the biology in downstream experiments. Another industry-wide challenge is the need for novel therapeutic targets since most biopharma companies are working on the same, stagnant targets. As technologies have advanced, companies like Envisagenics can look beyond the targets at the genetic level by taking an exon-centric approach. With this validated approach, Envisagenics has created one of the largest search spaces of approximately 7 million splicing events, consisting of novel, alternative splicing-derived proteins.
Compared with existing approaches, how unique and differentiated is your approach?
Maria: Envisagenics’ SpliceCore software platform uses machine learning and AI to re-envision the human genome with a validated exon-centric approach that leads to the discovery of novel targets that gene-centric discovery approaches cannot find. Envisagenics’ technology combines high-performance computing and proprietary ML algorithms to process high volumes of RNA-seq data for the identification of novel targets, at an accelerated rate, in the therapeutic areas of interest—thereby truncating a promising new drug’s time to market. Envisagenics’ technology also addresses the high failure rates of therapeutics in clinical trials by leveraging its scientific expertise in RNA splicing and combining it with SpliceCore’s ability to identify and develop highly specific therapeutics that modulate RNA splicing events involved in the pathogenesis of oncology, neurodegenerative, and metabolic disorders. With innovative technology and rare expertise, Envisagenics is poised to help patients faster than ever before.
In your opinion, what are the key challenges in realizing the full potential of your new technologies? Solutions? Do you anticipate any key milestones in the near future?
Maria: The primary challenge has been overcoming outdated, preconceived biases against RNA therapeutics and AI, along with a general resistance to change. Historically, the field of RNA therapeutics has had its setbacks, partly due to delivery methods and concerns with efficacy during development. However, the industry’s reluctance to embrace RNA therapeutics fell by the wayside with the advent of successful mRNA vaccines during the COVID-19 pandemic. RNA technologies have now demonstrated enormous promise, and we are energized and excited to be part of that revolution. As the company continues to mature, Envisagenics’ goal is to see one of its RNA therapeutic assets help patients in need faster than ever. There are other AI-based biotechnology companies that are approaching IND and taking drugs into the clinic. Therefore, our goal represents a key, achievable milestone that Envisagenics aspires to reach in the coming years.
AI/ML is core to Envisagenics’ platform. How do you see these novel data technologies becoming the norm in R&D in the next couple of years?
Maria: Recently, one of the biggest shifts within Biopharma is that AI/ML has gained a greater following among both scientists and business-minded executives. Envisagenics is proud to be a part of this innovation. We announced our collaboration with Bristol Myers Squibb on November 29, 2022. The multi-year partnership aims to leverage our proprietary AI technology, SpliceCore, to identify alternative splicing derived targets for therapeutic development in the oncology pipeline at BMS. While we hope to continue to see similarly structured partnerships between Big Pharma and Biotech AI, at the same time, novel data technologies continue to be introduced to the market that improve R&D insight, efficiency, and speed in the pursuit of better treatments. At some point, companies that fail to embrace AI/ML will be left behind, and the industry has taken notice. Therefore, in the next few years, AI/ML will become a standard component of Biopharma R&D pipelines.
Many Biopharma companies already partner with agile, specialized AI/ML companies in order to gain access to next-gen technologies while also standing up small, internal Data Science teams. Big Pharma has also begun to reserve capital and infrastructure for the pursuit of internal in-silico capabilities to maximize the value of internal, proprietary databases.
While we are still in the early days of Biopharma AI/ML, we have already seen new technology embraced both internally and externally throughout the Biopharma industry. We expect these adoption trends to continue in pursuit of innovation, and we predict that R&D pipelines will transform permanently, to the benefit of patients around the world.
Thank you, Maria, for your insights. You mentioned collaboration between big pharma and biotechs. What does global collaboration mean to your company?
Maria: Diseases affect patients worldwide, and effective treatment development requires a global outlook. For Envisagenics, “global collaboration” means working with likeminded companies to take an expansive, inclusive approach to problem solving. Internally, it means that we must seek and develop diverse datasets that train ML models and do so in concert with diverse scientific expertise while recruiting the best talent from around the world to work for us. It also means that we must support and strive for equal access to treatments among patients. Externally, it requires us to seek input, ideas, and data sources from around the world and push ourselves to adopt new approaches without bias, regardless of where those ideas originate. As a result, Envisagenics maintains a focus on making the biggest impact it can for patients.
Fortunately for Envisagenics, our principal technology—the cloud-agnostic SpliceCore software platform—can be deployed to collaborate with anyone, anywhere, in a secure and compliant manner. This has allowed us to work with some of the pre-eminent global Biopharma companies, such as Bristol Myers Squibb, Johnson & Johnson, and Biogen.
Thanks again Maria!
Dr. Maria Luisa Pineda started as a high school Intel International Science Fair winner. For her undergraduate studies, Dr. Pineda was awarded an endowment of $2 million dollars from the Goizueta Foundation and an NIH fellowship with the Minority Access to Research Careers (MARC U*STAR) program. Dr. Pineda received her Doctorate from the prestigious Cold Spring Harbor Laboratory School of Biological Sciences as an Arnold and Mabel Beckman graduate student and a William Randolph Hearst foundation scholar. After graduating, she acquired investment experience in technology and life-sciences startup companies at Canrock Ventures and Golden Seeds, LLC. Under her leadership, Envisagenics has received non-dilutive SBIR grants from the National Institutes of Health, raised capital from investors, won several prestigious artificial intelligence competitions, and formed multiple research collaboration partnerships with Biopharma.