Artificial intelligence (AI) is transforming every aspect of our life. It’s been said that one of the biggest opportunities for AI is the healthcare industry, spending on which is forecasted to jump from $2.1 billion to $36.1 billion by 2025¹. At Scale Asia Ventures, we focus on AI-powered biotech and health tech startups, particularly in the field of drug discovery and application of advanced multi-omics technologies.
Drug discovery has historically been a long and expensive process with high risk. Traditional drug discovery typically costs up to $1.5–2B and 15 years per medication. Patent cliffs faced by many big pharma are also driving the transformation of drug discovery. With increasing volume of data, advanced ML/DL algorithms and improved computing power, AI can now facilitate drug discovery, from identifying candidates, to conducting clinical trials, to publishing data.
We believe in startups with innovative AI technologies, access to robust reliable data and cross-disciplinary team. Top AI drug discovery startups like Atomwise, Insitro, Insilico and Benevolent are all empowered by strong deep learning algorithms.
Multi-omics data include genome, transcriptome, proteome, epigenome, metabolome and microbiome. By integrating these complex omics data, we could find novel associations between biological entities, pinpoint biomarkers of disease and physiology. At Scale Asia Ventures, we identified three areas of interest in the field of multi omics:
- ‘Omics-facilitated early cancer detection in liquid biopsy
- Precision cancer treatment based on multi-omics data
- Microbiome-based precision medicine
Next we would like to introduce Kernal Biologics, an MA-based messenger RNA (mRNA) company that is developing COVID-19 vaccines and cancer therapeutics.
The central dogma of molecular biology was a demonstration of the flow of genetic information basically described as: DNA -> RNA -> protein.² It is the key link in the process of translating genetic information encoded in DNA into instructions that are used by cells to produce the proteins needed to carry out essential cellular functions. mRNA therapy is engineered to deliver mRNA encoding natural, functional proteins that replace defective or missing proteins. Simply put, it’s like a platform that instructs specific cells to naturally make their own medicine. With many years of development and refinement of RNA technology, mRNA-based therapeutics and vaccines are finally entering clinical stages.
Kernal is developing their proprietary platform that decreases immunogenicity upon existing mRNA technologies and enables cell-specific therapeutic protein expression. The two key challenges faced by current mRNA therapies could be solved by Kernal’s patented mRNA technologies:
1. Insufficient protein production for therapeutic benefitKernal’s patented stealth mRNA technology removes immunogenicity sequence features and leads to more abundant protein synthesis.
2. Expression is not limited to specific cellsTo realize targeted expression, Kernal interrogated translatome data from normal and cancer cells, and discovered mRNA sequence features that enable cancer cell specific translation using deep learning algorithms.
We believe that Kernal’s proprietary platform with unique methods of codon-engineering and smart design would enable the company to stay in the forefront of mRNA medicine.
While the COVID-19 outbreak is now spreading rapidly around the world, leaving a path of devastation in its wake, mRNA treatment is a sector that might actually benefit from this pandemic. Moderna’s MRNA-1273³ and Pfizer’s and BioNTech’s BNT162b2⁴ both adopt mRNA-based approach mmunizing against SARS-CoV-2. The mRNA technology has shown advantages in speed and manufacturing in vaccine development. Benefited from these established players and their experiences, Kernal is also leveraging its technology against Covid and getting promising in-vitro experiment results.
Looking beyond Covid headlines, Kernal is also applying its technology to the emerging field of cancer immunotherapy for a more sustainable future. mRNA-based cancer vaccines and therapeutics can deliver custom-tailored medicine for individual patient. Initially going after acute myeloid leukemia (AML) which is associated with the lowest survival rates among all hematologic malignancie, Kernal is expanding into other cancer types with significant unmet medical need like lung cancer with its unique onco-selective mRNA approach.
Kernal Biologics was founded by four young scientists with diverse background including synthetic biology, immune-oncology and deep learning. The Co-Founder Yusuf Erkul has been focused on cancer research since his undergraduate study at MIT. Before going back to medical school to become a physician, he joined Merck & Co.’s oncology department as a scientist and was focused on RNA based drug discovery there. The other co-founder Burak Yilmaz is also a scientist focused on synthetic biology as well as an entrepreneur. He founded Sentegen Biotech in 2010, which manufactures synthetic genes, oligonucleotides, and diagnostic probes, and later decided to establish Kernal with Yusuf.
Currently in MassBio’s MassConnect Program, Kernal was once a member of MIT Startup Excahnge and Y Combinator, winner of Amgen’s Golden Ticket, and was selected to join 2018 MassChallenge. These awards and experiences help Kernal accumulate resources and access to industry experts and veterans for mentorship and advice.
At Scale Asia Ventures, we harness intelligence and technology. In the field of health tech, we believe there has never been a more exciting time to invest in science. New tools such as genomic sequencing, multi-omics techniques, precision medicine therapies are producing true advances for patients. The key to success in biotech investing is being able to identify where scientific advanced are having the biggest impact on patients’ lives, and we believe this is also what Kernal is pursuing.
1. Intelligent biopharma. (2019, October 3). Retrieved September 23, 2020, from https://www2.deloitte.com/us/en/insights/industry/life-sciences/rise-of-artificial-intelligence-in-biopharma-industry.html
2. Leavitt SA (June 2010). “Deciphering the Genetic Code: Marshall Nirenberg”. Office of NIH History. Archived from the original on 2015–03–17. Retrieved 2012–03–02.
3. Moderna’s Work on a COVID-19 Vaccine Candidate. (2020). Moderna. https://www.modernatx.com/modernas-work-potential-vaccine-against-covid-19
4. “Pfizer and BioNTech Choose Lead MRNA Vaccine Candidate Against COVID-19 and Commence Pivotal Phase 2/3 Global Study.” Pfizer, www.pfizer.com/news/press-release/press-release-detail/pfizer-and-biontech-choose-lead-mrna-vaccine-candidate-0.