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Which drugs will work for your patient subgroups?

Effective innovation, R&D productivity, and hitting sales forecasts all depend on knowing which drugs will work in which patient subgroups.

Many of the most expensive late-stage clinical trial failures are due to the inability to show sufficient clinical efficacy. This is often a failure to recruit the right patients who will respond to a drug targeting a specific mechanism.

Even when approved, getting a new drug prescribed and defending a price point in an outcomes-based remuneration model requires biomarker-based tools to identify people who are most likely to benefit from a treatment.

Accurate patient stratification is fundamental – it helps choose the right target product profile and generates mechanistic biomarkers that accelerate and de-risk clinical development and product launch.

90%

of drug candidates failed in the last decade 1

57%

of phase III trial failures are due to lack of efficacy 1

67%

10-year increase in development costs 2

57%

10-year decrease in peak sales forecast 2

1. Hwang TJ, et al. Failure of Investigational Drugs in Late-Stage Clinical Development and Publication of Trial Results. JAMA Intern Med. 2016 Dec 1;176(12):1826-1833
2. Deloitte 10 Years On: Measuring Return on Pharma Innovation (2019)

 

 

Understand disease biology better

By detecting vastly more signal than other drug discovery approaches, our combinatorial analytics approach reveals the drivers of disease biology for patient subgroups at a level of detail that nobody else can achieve.

Our analyses generate deep mechanistic disease insights - discovering novel drug targets and leads for unmet medical needs, finding opportunities to use existing drugs to treat additional diseases, stratifying potential responders, and giving major competitive advantages.

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Solutions and partnering opportunities

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Novel target discovery

Gain translational discovery advantage and select targets with companion biomarkers matched to patient biology

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Indication extension

Maximize portfolio returns with precision repositioning of assets with companion stratification biomarkers

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Clinical trial analysis

Identify drug response biomarkers from analysis of Phase III clinical trials patient efficacy data

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Portfolio review

Reevaluate shelved programs to bring forward new medicines and maximize the ROI from sunk R&D investments

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Patient stratification biomarkers

Our mechanism-based PSBs are unique, patentable IP that capture mechanistic insights into the mapping of causative disease biology to patient subgroups.

These hypothesis-free disease insights go far beyond traditional genetic analysis approaches and enable us to identify novel causal drivers of disease biology and accurately predict potential responders based on the mechanistic causes of their disease. 


Avoid late-stage efficacy failure
Design more effective clinical trials
Develop drug response biomarkers
Identify secondary indication potential
Review and recover shelved drug programs