The drug discovery community has been plagued with problems for decades. There are high failure rates since it’s so difficult for current technologies to target factors that are specific to the individual patient. NowProteorexaims to solve this problem with their power-packed mix of machine learning, patient-derived cell-based screening, and Artificial Intelligence for discovering therapeutics that properly match a patient’s needs. The company’s co-founder and CEO, Aman Iqbal, talked specifics:
Where did your team first get together, and when did you decide to start a company?
AI: The Proteorex team first met in Toronto, a city where the winters are only slightly colder than San Francisco’s summers. Our core team is composed of experienced and driven members with expertise in pharmaceuticals (e.g., Astex Pharmaceuticals), academia (e.g., Oxford, University of Toronto), venture capital (e.g., Cambridge Innovation Capital), and strategic consulting (e.g., Boston Consulting Group). Our diverse experiences across the drug development, drug discovery, and life sciences spectrum drew the team together to discover novel therapeutics for diseases with the highest unmet need, pushing the boundaries of drug discovery through innovative and world-class science.
What problem are you aiming to solve with Proteorex?
AI: Only 10% of the human genome has been targeted for drug development and only 1350 new chemical entities are available to the world. Current drug discovery projects suffer a failure rate of 95%+ and rely on technologies with severe limitations. Challenging drug targets (e.g., protein complexes) are largely ignored by Big Pharma. In addition, Big Pharma’s traditional screening approach has only identified bulky hits, resulting in clinical failures. The flawed focus and failures have left patients in the perilous position of not receiving effective treatments.
Proteorex is disrupting the biopharmaceutical industry and treating diseases by solving the major problem faced by the industry: the lack of new medicines that are not targeted to patients, and are time consuming and expensive to bring to the market.
How does your technology work?
AI: Our team is developing an integrated drug discovery technology platform that has the following three components:
- Proprietary and AI driven drug design technology that rapidly produces drug-like small molecules in a fraction of cost and time than all conventional small molecule drug design technologies
- Patient derived cell based screening on microfluidics chip based technology to identify patients that will benefit most from the therapeutic. The throughput allows us to carry out cell-based experiments such as gene knock ins and knock outs while screening for therapeutic combinations. This is a feat no one has been able to achieve to date. A machine learning approach may be developed to sift through data
- Bioinformatics and machine learning methodology that will allow us to link rare diseases to patients and drug targets. Machine learning for drug development will allow us to rapidly convert a small molecule lead into a drug candidate through the emerging one-shot low data approach
The therapeutics will be single agents (small molecule drugs), combination of a small molecule and antibody, antibody-drug conjugate, stem cell therapeutic, and cell-based therapeutics that will enhance the treatment efficacy for individual patients with a clear focus on finding cures.
How did you become interested in science?
AI: Each member of our team possesses a PhD degree in the sciences. We were driven to pursue the sciences either through a personal connection (e.g., a sick family member), through a desire to be intellectually challenged, or to explore the unordinary. Nonetheless, what brings us together is the unmatched passion to push the frontiers of the known world, and to make contributions that save lives.
What lessons did you learn transitioning from science to entrepreneurship at IndieBio?
- Show and tell people the impact of your company/product/technology. This is not an “either/or” exercise, because you cannot assume your audience will have the same perspective as you have.
- Have strong opinions, but remain open to feedback and other viewpoints.
- The goal lines in business and entrepreneurship can be fluid. Be ready to pivot and adjust at a moment’s notice.
- You will have setbacks, like a broken leg or a stalled deal, but no matter what, you must find at least one way, every day, to drive your business forward.
How do you think your success as a company would change the medical industry?
AI: Proteorex seeks to be the first drug company to combine chemical synthesis and the drug candidate discovery process, personalized patient biology, with impactful, efficacious drug identification by utilizing machine learning. Our vision is to transform the drug discovery process by producing therapeutics (single or combination, Phase 1 ready) from target ID per disease for a patient in less than a year.
What are the milestones you’re looking to hit in the near future?
- Fundraising: Close a seed-series round to drive our lead drug development programs to first-in-patient clinical trials
- Internal projects: 1) Pre-clinical package for our lead, orally-available, small molecule drug to treat re-arranged mixed lineage leukemia (rMLL) and acute lymphoblastic leukemia (ALL). 2) Orphan disease status for our lead rMLL/ALL program. 3) Mouse proof-of-concept for our aggressive glioblastoma program.
See Proteorex pitch at IndieBio Demo Day on September 14th in San Francisco or via Livestream!Register here.
Pictured above: The Proteorex team.