Transforming Pharmaceutical R&D with Data: 2017 Research Explores if Current R&D Economics are Unsustainable

Dublin, July 20, 2017 -- The "Transforming Pharmaceutical R&D with Data" report has been added to Research and Markets' offering.

In the current drug pricing environment, biopharmaceutical firms cannot afford to continue spending billions of dollars on development programs that are more than 90% likely to fail. Raising prices to compensate for expensive, risky research and development (R&D) is no longer an option amid a global payer backlash against drug costs. Drug R&D needs to become more efficient, faster, and cost-effective in order for biopharma firms to be sustainable and to maintain a supply of innovative treatments.

Fortunately, multiple new tools are emerging to help streamline R&D. Most of these involve more intelligent and targeted use of existing data, and exploiting multiple new kinds of data and analytical methods. They are enabling efforts along the R&D value chain, from discovery through late-stage trials and approval.

Several Big Pharma companies have started to invest in more efficient processes such as e-sourcing clinical data and virtual trial recruitment. Precision medicine, which is growing rapidly in oncology, in theory allows smaller, more targeted trials with a higher chance of success. Meanwhile, technology giants like IBM, as well as a new generation of biotechs, are using artificial intelligence and machine learning to accelerate and improve R&D; many are seeking partners as well as developing their own pipelines. Regulators are very open to new, faster, data-driven approaches to drug development.

Making R&D more efficient will not solve the drug pricing challenge; however, it will help by allowing biopharma to run a wider set of programs and make faster, wiser decisions about when and whether to engage in expensive late-stage trials.

Key Topics Covered:

1. Executive Summary

• Current R&D economics are unsustainable
• Accelerating discovery
• Accelerating development
• Accelerating approval, access, and adherence
• Challenges to data-driven R&D streamlining

2. Current R&D Economics are Unsustainable

• The drug pricing environment is forcing more efficient R&D
• New tools are emerging from discovery through to commercialization
• Driving R&D efficiency requires partners
• Squeezing value out of forgotten assets
• Cost and time savings may reach 20-50%

3. Accelerating Discovery

• Faster identification and validation of promising drug targets and leads
• Accelerating discovery with artificial intelligence
• Augmenting, not replacing, the work of scientists
• Up-ending drug R&D
• Big Pharma is signing up for computer-backed discovery
• How predictive is your AI algorithm?
• Machine-accelerated drug discovery is still only a promise
• Precision medicine and biomarkers

4. Accelerating Development

• Improving and accelerating clinical trials
• Data driven site-selection
• Accelerating trial recruitment
• Electronic trial data capture

5. Accelerating Approval, Access, and Adherence

• Expediting the regulatory process, drug uptake, and adherence
• Accelerating regulatory review
• Faster commercial uptake
• Outcomes data inform R&D as part of a broader, data-driven disruption

6. Challenges to Data-Driven R&D Streamlining

• Regulatory uncertainty
• Data compatibility
• Organizational and cultural change
• Pharma must upgrade its data skills to stay competitive

For more information about this report visit https://www.researchandmarkets.com/research/lt5w8l/transforming

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         Related Topics: Drug Discovery