Boosting R&D Productivity

The pathway to a development candidate is rarely straight and smooth. A recent McKinsey article detailed some of the challenges faced by R&D organisations in biotech and pharmaceutical companies in that journey, and some of the initiatives being undertaken across the industry.

Industry reports like these tend to focus heavily on the "D" and not really the "R" when describing the ways in which companies can improve productivity. To be fair, the development end of the business tends to be more public, and therefore gets more scrutiny. Nevertheless there were some interesting takeaways from the article, which I invite you to read here.

What was perhaps most compelling about the article were 4 key characteristics of the High-performance R&D delivery engine (outlined in red) and the initiatives that the industry is undertaking in those areas to improve performance. Since the article has a more development-oriented slant to it, we've taken a more discovery-oriented slant in this article and provided some examples that show how our Pipeline platform can be used to support those initiatives.

Simplified, Automated, and Digitised Core Processes

Simplified, automated, and digitized core processes can boost R&D productivity by:

• Reducing the time and effort required to perform routine tasks. For example, automated data entry and analysis can free up scientists to focus on more complex and creative work.
• Improving the accuracy and consistency of data. This can lead to better decision-making and reduced risk of errors.
• Facilitating collaboration and communication among researchers. This can help to break down silos and speed up the development process.
• Providing real-time insights into the R&D process. This can help to identify potential problems early on and make adjustments as needed.
• Enabling more efficient use of resources. This can help to reduce costs and improve overall productivity.

Some specific examples of how simplified, automated, and digitized core processes can boost R&D productivity include:

• Electronic lab notebooks (ELNs) can help scientists to track their experiments and data more efficiently.
• Automated data analysis tools can help scientists to identify trends and patterns in their data more quickly and easily.
• Collaborative software platforms can help scientists to share data and ideas with each other more easily.
• Real-time monitoring systems can help scientists to track the progress of their experiments and identify potential problems early on.
• Inventory management systems can help scientists to track and order supplies more efficiently.

By simplifying, automating, and digitizing core processes, R&D organizations can improve productivity, reduce costs, and accelerate the development of new drugs and therapies.

Pipeline’s workflow-oriented modules make it possible for research teams to create and manage workflows and receive real-time notifications as things change. Each step in the workflow supports threaded communication making collaboration easier and less siloed. Pipeline’s Inventory module is integrated into Protein Production and Chemistry workflows, making it possible to register proteins (and other biologics) and compounds and place them into inventory from within the workflow itself. The scientist never has to leave their current workflow in order to manage their inventory.

Pipeline’s Field Library allows scientists to use industry standard vocabularies when recording and sharing data, thereby improving data quality and consistency both within the organisation and when working with CROs and service partners.

We’re also seeing biotech companies hit certain inflection points where it becomes more cost-effective and efficient to bring automated compound synthesis in-house. Here it’s essential to be able to plug-in support for different liquid handlers, and weighing robots in a manner that lets these systems decompose a high-level compound library request into a series of automated requests for building blocks, reaction protocols, liquid dispensing operations, etc.

Enabling the R&D System to Boost Productivity

In addition to simplifying, automating, and digitizing core processes, R&D organizations can also boost productivity by enabling the R&D system. This includes making improvements in decision-making, footprint, and organization.

Decision-Making

• Empower scientists to make decisions: Give scientists the authority to make decisions about their work, without having to go through multiple layers of management.
• Use data to drive decisions: Make decisions based on data and evidence, rather than on gut feeling or politics.
• Create a culture of innovation: Encourage scientists to take risks and think outside the box.

Footprint

• Optimize the R&D footprint: Ensure that the R&D footprint is aligned with the organization's strategic goals.
• Collaborate with external partners: Partner with universities, research institutions, and other companies to access new ideas and technologies.
• Leverage technology: Use technology to connect and collaborate with researchers around the world.

Organization

• Create a lean and agile organization: Remove bureaucracy and streamline processes to make the R&D organization more efficient.
• Foster a culture of collaboration: Encourage scientists to work together across disciplines and departments.
• Develop leaders: Invest in the development of R&D leaders who can create a high-performing culture.

By enabling the R&D system, organizations can create an environment that is conducive to innovation and productivity. This will help to accelerate the development of new drugs and therapies, and improve the lives of patients.

Pipeline’s Planning module allows scientists to create goals for drug discovery projects and to align their activities with those goals. The Target Product Profile helps the team focus on a Minimum Viable Product (MVP). The GRIDALL implementation helps the team devolve a high-level set of Goals into a set of identified Risks, Issues, Decisions, Actions and Lessons Learned and allow the team to chart a clear course to that MVP.

Pipeline’s Field Library and Workflow Builder allows users to customise their workflows and gather critical information needed to facilitate data-driven decision making.

Pipeline’s notifications, activity feed, and communication threads help improve communication, collaboration and real-time awareness of project and activity status. It makes more of the work of drug discovery transparent at every level of your organisation from the lab to the leadership team.

Next-generation Data, Analytics, and Technology

Next-generation data, analytics, and technology can improve R&D productivity in a number of ways:

• Data integration and management: Next-generation data integration and management tools can help R&D organizations to collect, store, and analyze large volumes of data from a variety of sources, including electronic lab notebooks, clinical trials, and real-world evidence. This can help to improve the accuracy and consistency of data, and make it easier for scientists to identify trends and patterns.
• Artificial intelligence and machine learning: Artificial intelligence (AI) and machine learning (ML) can be used to automate complex and time-consuming tasks, such as data entry, data analysis, and hypothesis generation. This can free up scientists to focus on more creative and strategic work.
• Real-time monitoring and predictive analytics: Real-time monitoring and predictive analytics can help R&D organizations to identify potential problems early on and make adjustments as needed. This can help to reduce the risk of costly delays and failures.
• Collaboration and communication: Next-generation collaboration and communication tools can help R&D organizations to break down silos and speed up the development process. This can be especially helpful for organizations that are working with partners or have employees located in different parts of the world.
• Virtual and augmented reality: Virtual and augmented reality (VR and AR) can be used to create immersive and interactive experiences for scientists. This can help to improve training, visualization, and data exploration.

By leveraging next-generation data, analytics, and technology, R&D organizations can improve productivity, reduce costs, and accelerate the development of new drugs and therapies.

Informatics environments tend to consist of applications that generate disconnected islands of data. Pipeline’s plugin-oriented architecture allows companies to leverage the investments that they’ve already made in ELNs, registration systems and inventory management systems and integrate these systems and their data together. The Field Library allows the user to map data from one system to another, and in the process map the data to a standard ontology, thus helping to ensure data consistency.

The initial hurdle that all AI/ML initiatives face is data standardisation. We have to have clean, consistent data sets in order to create accurate models. The challenge here is that each system may refer to a given field of data differently. Pipeline’s Field Library provides that consistency across the system that is essential for any AI/ML implementation. Moreover, the built-in Calculation Engine allows scientists to apply AI/ML models to data in the system.

Streamlined Vendor Partnerships

Streamlined vendor partnerships can improve R&D productivity in a number of ways:

• Access to expertise and resources: Vendors often have specialized expertise and resources that can be leveraged by R&D organizations. This can help to accelerate the development process and improve the quality of research.
• Reduced costs: Partnering with vendors can help to reduce costs associated with R&D, such as the cost of equipment, software, and personnel.
• Improved efficiency: Streamlined vendor partnerships can help to improve efficiency by reducing the time and effort required to procure goods and services. This can free up R&D staff to focus on more productive activities.
• Increased innovation: Vendors can often provide R&D organizations with access to new technologies and ideas. This can help to foster innovation and lead to the development of new products and services.
• Improved compliance: Vendors can help R&D organizations to comply with regulatory requirements and industry standards. This can help to reduce the risk of costly delays and fines.

Overall, streamlined vendor partnerships can play a vital role in improving R&D productivity. By leveraging the expertise, resources, and capabilities of vendors, R&D organizations can accelerate the development process, reduce costs, and improve the quality of their research.

Pipeline’s PharmExchange service makes it possible for researchers to create workflows capable of requesting services from CROs and service providers, exchanging data with them and tracking the progress of those requests in real-time. Many of these collaborations will fail because of a breakdown in trust. To mitigate this risk, it's essential for biotech companies and CROs to share not only basic metadata about an assay (for example descriptions of the fields of data being exchanged), but also protocol information about the assay that describe how those data were generated or computed.?

Combined with the Planning module, scientists can estimate the costs involved with executing certain workflows where selected steps are performed by CROs. The Planning module can help scientists estimate compound and protein requirements for screening cascades.

If you'd like to learn more about Pipeline and how it can transform your R&D organisation contact me Mark Fortner