Boston-based Scipher Medicine, which wants to ensure that patients get access to drugs that work effectively from day one, raised a $10M Series A round led by Khosla Ventures in September 2018. With its clarion call of “stop taking drugs that don’t work”, the startup is aiming to create a new paradigm in drug development.
Co-founders Dr. Albert-László Barabási and Dr Joseph Loscalzo argue that a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular network. This means that diseases can be connected to each other if there is a common gene associated with them. An obvious example would be diabetes and obesity where the common genetic occurrence mean that if you have one, you’re highly likely to develop another.
Barabási and Loscalzo infer that this cellular interconnectedness suggests that better human interactome (a whole set of molecular interactions in a particular cell) maps could “lead to identification of disease genes and disease pathways, which, in turn, could offer better targets for drug development”. If the links between diseases are uncovered, it could help understand co-morbidity or why certain group of diseases occur together.
It could then, naturally, open the door for novel approaches to disease prevention, diagnosis, and treatment. Largely, it would “reshape clinical practice”, create a way for “better disease classification” and “personalize therapies and treatment” in a uniquely different way than tech-first healthcare startups like K Health.
Personalized treatment is at the core of what Scipher Medicine wants to do.
Dr. Barabasi and Dr. Joseph Loscalzo have spent 10+ years building and interpreting this human interactome which explains how “proteins expressed from the human genome interact to cause specific disease phenotypes”. While the company hasn’t launched its product yet, the company’s CEO Alif Saleh said, “With the completion of this financing round, we are accelerating product development and plan to announce our first product before the end of the year. Our partnership with Khosla Ventures will be instrumental in ensuring that our technology and platform is commercialized to the benefit of patients, providers and payers.”
The Future of Patient Treatment
The US alone holds 45%+ of the global pharmaceutical market, pegged at around $446Bn. Out of this, pharmaceutical companies spend, on average, about 17% of revenues on research and development (R&D). However, the drugs developed try to address symptoms for average populations, keeping the market in mind. There’s also an emphasis on blockbuster drugs—medicines that can generate global sales of at least $1Bn annually—along with a focus on trying drug after drug until something works. This is especially dangerous as, according to The Tufts Center for the Study of Drug Development, the development and marketing approval for a new molecular entity takes 13+ years and around US$2.6Bn.
Scipher Medicine therefore is aiming to predict if a patient will actually respond to a particular drug therapy. “Two-thirds of patients who are prescribed drugs,” the startup’s website claims, “don’t respond adequately to the treatment, resulting in billions of dollars wasted on ineffective therapies and health care, leading to an unprecedented burden on patients, hospitals and payers.”
The situation gets even more problematic when it comes to complex diseases which are governed by weak genetic links and strong environmental factors. In the case of autoimmune diseases, according to Scipher Medicine, drug response rates are falling below 20%. But healthcare should not be a process of trial and error which costs billions of dollars and fails to alleviate pain despite that. Does the solution, then, come in the form of right targets and right drugs which can improve efficacy?
The Use Of Network Medicine
Dr. Barabási has coined and popularized a term called “network medicine” which applies network science towards identifying, preventing, and treating diseases and utilizes biological networks such as protein-protein interactions and metabolic pathways. Network-based study is important, Dr. Barabási and others argue in this paper, because “traditional drugs lack selectivity towards the genetic cause of the disease, targeting instead the symptoms of the disease.” This is especially relevant when recent studies “demonstrate that the genes associated with a disease tend to cluster in the same network neighborhood, called the disease module”. In fact, their analysis of 238 drugs used in 78 diseases indicates that the therapeutic effect of drugs is localized in a small network neighborhood of the disease genes.
How Scipher Medicine Works
The Scipher Medicine platform allows for blood and tissue tests to be taken at a routine doctor’s visit to predict if your drug response will be adequate or not. Then, through the interpretation of RNA or protein expression data from the patient’s blood or tissue sample, it reveals the underlying molecular process regulating the disease. After this, drugs are screened to determine which therapy actually targets the disease in order to accurately predict patient response. Simply, the platform identifies which drug will work for you based on your disease biology (not an average patient’s), based on your symptoms and disease classification.
For example, Scipher Medicine claims, “In rheumatoid arthritis, if our test was ordered before prescribing 100% of all anti-TNF drugs in the United States, it would double drug response rates from 35% up to 67% while saving over $4.7 billion by avoiding unnecessary treatment and health care costs, and ensuring patients receive the best care from day one.”
The fact that blood and tissue tests taken at a routine doctor’s visit can predict if the drug actually works can change how healthcare operates around the world. Once practised, it can make way for the prescription of the most effective treatment which can result in faster recovery and reduced healthcare costs.
But the innovation doesn’t end there: As the molecular data generated by Scipher Medicine’s tests can then used to fuel novel target discovery. Simply, in patients who don’t respond to existing therapy, it can—by addressing a clear unmet medical need—accelerate drug development.