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Winchester, MA, United States

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Agency: Department of Health and Human Services | Branch: National Institutes of Health | Program: SBIR | Phase: Phase II | Award Amount: 469.94K | Year: 2016

DESCRIPTION provided by applicant Drug development is a very lengthy and expensive undertaking Failure rate for novel drugs exceeds Therefore successful drugs must cover the costs of these failures As such prescription drug prices have escalated at an alarming rate and show no signs of stopping The need for successful drugs to cover failures also means that pharmaceutical companies primarily devote resources to pursuing drug candidates that have a large enough population to allow the company to earn a return on its investment Thus diseases that affect only a small portion of the populace are not investigated nearly as much as say oncology cardiovascular or immunology Current practice usually involves taking modeling techniques developed for small molecule research and trying to adapt them to biologics However this approach more often than not does not provide the scientist with predictions around feasibility and optimal drug properties resulting in wasted effort pursuing leads that have no chance of making it through clinical trials or to be reimbursed by payors Applied BioMath has developed tools that address high value questions in the middle of the drug development pipeline By coupling quantitative systems pharmacology techniques with high performance computing and sophisticated mathematical algorithms we have proven an ability to predict optimal drug properties years before entering the clinic For the past two years we have been offering our services to pharma and biotechs alike to rave reviews We have also been approached with inquiries to license our software This project will fund the development of our proprietary algorithms and toolsets into a stable standardized software platform that can be automatically validated for GLP for by biologics to develop their internal systems pharmacology models At its heart our toolsets are built on Kronecker Bio an open source biophysical computational engine co developed by one of our Founders while pursuing his PhD in Biological Engineering with the Computer Science and Artificial Intelligence Lab from the Massachusetts Institute of Technology This robust platform is currently in use in its raw form in the pharmaceutical industry but is limited in its adoption due to its lack of usability quality contro and GLP validation This project will focus on the application and presentation layer allowing the underlying computational functionality to be easily accessed utilized and understood so capital requirements are less than a typical software development project Achieving our goal of building this software platform is only the first step What follows is a concerted push into the biologics segment which we are currently seeding through our services offering and gaining a reputation as a firm that delivers high value on time We have completed our second round of fundraising raising a total of $ m between both rounds This grant plus the additional fundraising will ensure that we are able to roll out our tools and assist drug companies in delivering best in class biologics that meet unmet medical need on an accelerated timeline to provide patients with a better quality of life Better faster cheaper drugs truly a win win in PUBLIC HEALTH RELEVANCE To reduce the cost of drugs identify fast failures and accelerate the rollout of best in class biotherapeutics analyses in the middle of the drug development pipeline from LI to early clinical trials based on mechanisms and biophysics is needed There are currently a number of open source tools that provide systems pharmacology models for use in research However a lack of a standardized and automated GLP validation scheme prevents the models from continuing through to development A robust systems pharmacology software platform widely utilized by drug companies and upon which fit for purpose systems pharmacology models can be built will greatly reduce the time required to get a drug to market enable the development of best in class drugs increase safety for patients and significantly reduce the development costs associated with biologics We have developed proprietary mechanistic algorithms that we currently use to analyze assays and drug program data for our customers These algorithms are naturally grouped into certain functions toolsets These tools are applicable depending on what questions are being investigated across most all therapeutics areas While our toolsets InVitro Analyzer Biologic Feasibility Biologic Optimizer Biologic PKPD Biologic Mechanistic Covariants are currently in alpha stage being used to create fit for purpose models for our clients they are being used in industry to fulfill our servces contracts We are looking to create an industry standard platform leveraging our proprietary algorithms and toolsets that will allow drug scientists to create fit for purpose models that can be easily validated for GLP use in IND applications We have sampled the market and estimated a potential target audience of over users worldwide We arrived at this number by reviewing the Top Pharma companies by revenue determining employee count from those companiesandapos annual reports using our Founders knowledge of select large and small pharma and biotechs and its employee count and number of employees that could use our software segmenting the list into groups based on revenue extrapolating on a percent basis each companyandapos s applicable target audience assumed companies outside the Top had one quarter of the applicable audience as the th largest company and then summed these estimates This produced a number of over potential customers For validation we determined that the number of people globally employed in the pharmaceutical industry is www statista com So our target market is less than of total pharma employees and our business model shows market penetration of just over of our target market by or less than of total pharmaceutical employees


Applied BioMath | Entity website

Applied BioMath is currently seeking a talented and innovative PrincipalScientist or Senior Scientist to join our team inLincoln, MA, (the Cambridge area). The ideal candidate will work closely with Pharma and Biotech teams to develop, simulate, and visualize mathematical models to help drive decisions ...


Applied BioMath | Entity website

Pfizer Testimonial "Applied BioMath delivered exactly what we asked for in the timeframe agreed upfront. We were working towards a First in Human study deadline and we felt the integration of information that the systems approach provided was essential for our understanding of dose selection ...


Applied BioMath | Entity website

Applied BioMath was founded in 2013 by Dr. John Burke, Dr ...


Applied BioMath | Entity website

Goldberg, D. R ...

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