Open Scientific Innovation

Drug discovery time is lengthening and becoming more costly. Precision Medicine will shift the focus from blockbuster drugs to targeted therapies for smaller populations, which can reduce the market potential for each drug. This puts even more pressure on pharmaceutical companies to successfully deliver while reducing costs and time to market.

Open Scientific Innovation supports data-driven insight that is key to accelerate and improve innovation. Delivering on a highly integrated, streamlined information gathering and processing system that involves greater use of predictive technology, multidisciplinary project teams can connect to the highest quality information available at any time and any place. By unifying siloed applications and enabling seamless data management, scientists within the collaborative ecosystem across the globe can get to better insights sooner and reduce typical wet-lab experimentation. Managers can track project and program progression and performance and optimize the overall research program as needed. Researchers can now reap the benefit of accelerating and improving the quality of research programs while reducing costs.

Key Benefits:

• High quality and accessible information systems provide objectivity, replacing “opinion-based” decision-making
• Integrated collaboration systems democratize scientific knowledge across the organization
• Cloud-based information and analysis systems streamline externalized research partnerships

Unifying predictive science and experimental results to accelerate drug innovation design

The Life Sciences Pharmaceuticals industry faces a ‘new normal’ on the path to successful product development. With increasing operational costs, unsustainably high failure rates in development, and resulting poor quality candidates entering clinical phases, the pressure is on the industry to deliver better results that can drive down operational costs while reducing the time to market.

Therapeutics Efficacy and Safety processes accelerate innovation and reduce time to market in early stage pharmaceutical drug discovery and pre-clinical drug development by removing inefficiencies in discovery research. By applying in silico experiments in parallel with physical experimentation as part of an integrated, comprehensive rational drug design approach, researchers can prioritize the most commercially viable and druggable new entities faster.

The Therapeutics Efficacy and Safety process drives down operational costs and reduces time to market by calculating therapeutically relevant end-points, such as biological activity, toxicity, and ADME end-points within key decision support applications to aid design decisions and fast track the most promising candidates early in Discovery Research by enhancing the quality of candidates entering clinical studies.

Key Benefits:

• Reduce operational costs and speed up time to market with processes that improve efficiency in Discovery Research
• Fully profile drug molecules at the point of design
• Progress only the most promising candidates
• Improve efficiency in Discovery Research
• Improve the quality of candidates entering clinic

Predicting drug behavior to optimize manufacturing and delivery

Drug development is challenged in many ways. Physical testing is limited due to the very small amount of new active pharmaceutical ingredient (API) that is created initially. The FDA demands require maximum knowledge of drug behavior – referred to as “Quality-by-Design.” And late failure further downstream in clinical development and manufacturing is costly.

Molecular modelling can be used to maximize understanding of how an API will behave once it has been handed off from Discovery, thereby reducing the amount of API required for testing. Application areas for biologic therapeutics are potential aggregation, viscosity and solubility characteristics, for small molecule drugs growth morphologies and mechanical properties, for crystal and amorphous solid forms. Using downstream manufacturing data and specifications provide an understanding of the behavior of the therapeutic and thus satisfies Quality-by-Design criteria.

The prediction of critical manufacturability characteristics enables the design of optimal physical experiment parameter ranges and the parallel use of in silico experiments with physical experimentation forms an integrated, comprehensive rational drug development approach accelerating the development of novel drug candidates.

Key Benefits:

• Integrate Quality-by-Design methods to comply with regulations

• Improve hit-rate in clinical trials

• Improve efficiency in drug development

• Quickly explore new potential solid form delivery methods

• Select optimal liquid formulation platforms for therapeutic biologics