Platform

75% of Patients

Don’t respond to the world’s largest selling drugs: Anti-TNF Therapies 

Therapies are developed for the “average” patient, even though there is no such thing. As a result, patients are forced to try drug after drug until, hopefully, they find something that works. Meanwhile, they’re putting their lives on hold while their disease worsens, and billions of dollars are wasted annually in prescription costs. Scipher Medicine is going to change that through its unique approach to understanding disease biology that will ensure patients get the right treatment from day one.

 

PrismDx

We are building diagnostic tests that predict response to some of the most expensive drugs on the market that the majority of patients do not respond adequately to so that patients get the right treatment from day one, while saving the healthcare industry billions.

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PrismIx

We have built the world’s largest map of highly accurate protein-protein interactions that enables us to interpret individual patient’s gene expression data to better understand the biology of diseases, potentially uncovering new disease subtypes to help treat patients more effectively from day one.

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PrismDx

PrismIx

PrismDx

We are building diagnostic tests that predict response to some of the most expensive drugs on the market that the majority of patients do not respond adequately to so that patients get the right treatment from day one, while saving the healthcare industry billions.

Learn More

PrismIx

We have built the world’s largest map of highly accurate protein-protein interactions that enables us to interpret individual patient’s gene expression data to better understand the biology of diseases, potentially uncovering new disease subtypes to help treat patients more effectively from day one.

Learn More

Questions?

  • How is response defined?

    Response to drugs refers to a patient meeting his or her target goals. In rheumatoid arthritis, ulcerative colitis and many other diseases, it is defined as “low disease activity” or “remission”.

  • Why did Scipher focus its first Dx tests on predicting response to anti-TNF therapies?

    Anti-TNFs are currently the largest selling drugs in the world, yet only about one-third of patients who are prescribed these drugs respond adequately to them.1 In fact, 90% of RA patients are given anti-TNFs as a first line treatment despite the low response rate and incredibly high price tag. Patients put their lives on hold while their disease worsens and medical insurance companies and Medicare waste $9 billion each year in prescription costs (50%) and related expenses (50%). Scipher saw this clear need and built the tests needed to confront this problem.

  • How was Scipher’s platform developed?

    Scipher’s platform was the product of a 10-year collaboration between Joseph Loscalzo MD, PhD, Chief of Medicine at Brigham and Women’s Hospital, and Professor of Medicine at Harvard Medical School, and Albert-Laszlo Barabasi, PhD, Director of Northeastern University’s Center for Complex Network Research to build and interpret the first map that describes human disease biology. Brick by brick, they have assembled and interpreted the network of biological processes in human cells, using the most complete classification of protein to protein interactions and algorithms based on network science. Now, we’re able to decipher the biology of each patient’s disease and predict their response to specific treatments using their personal (individual) RNA data.2

  • How will Scipher find new therapies?

    By collecting RNA expression data from patients through its diagnostics, Scipher can identify similarities in the biology of patients who do not respond to current therapies to find new targets that haven’t been considered for RA or UC treatments. These targets can be validated on our platform to guide more effective drug development.3

  • Why did Scipher focus on RNA and proteins when building its map of human disease biology?

    While DNA is the static “blueprint” for all genetic information in every living organism, RNA converts this information to build proteins, the essential building blocks of all cells. RNA and proteins are dynamic and can change over time. When proteins are not produced and controlled correctly in our cells, diseases develop. Understanding how these proteins interact with each other gives us a stronger understanding of a disease’s biology. By combining RNA expression data with this map of protein interactions, we’ve been able to create our revolutionary new platform.2