Developing new drugs is complex, costly, and slow. Over the past decade, the average time for taking a new medication from candidate nomination to launch has been about 12 years, our research has shown. Understandably, pharma companies make strenuous efforts to optimize development, seeking to reduce cost per asset as well as time to launch. However, most of their efforts to date have focused on clinical development. Optimizing preclinical development—the process from candidate nomination to first-in-human (FIH) studies—offers significant value that has yet to be unlocked.
This untapped potential stems at least partly from the complexity of preclinical development. As research progresses from target identification through early discovery, experiments generate data that yields insights into a candidate’s structure, target-binding ability, modulation of targets, manufacturability, and other attributes. However, questions remain on matters such as potency, phenotypic stability, and toxicity, especially when teams are working with new mechanisms for molecules or new biological pathways that lack a well-proven association with a disease. A further complication is that decisions made during preclinical development—such as those concerning the design of animal studies—may need to take into account plans for downstream clinical trials.
Despite this complexity, leading pharma companies are finding ways to streamline processes and practices in preclinical development by identifying where value can be created and what changes they need to make to capture it.
Understanding the sources of value in preclinical development
Improvements in preclinical development can reduce costs as well as timelines, particularly when pursued across the full product portfolio to improve the main sources of value at this stage, which are: speed, simplicity, quality, and innovation.
Pharma companies can reduce the time they take to reach FIH application by 40 percent or more, with drugs progressing from candidate nomination to the start of clinical trials in as little as 12 to 15 months (exhibit). This not only provides patients with more rapid access to innovative medicines but also gives pharma companies earlier revenue flows and a longer period of exclusivity in the market.
For a pharma company seeking to move three to five investigational new drugs into FIH studies every year, an acceleration of nine to 12 months, applied across the portfolio, could translate into risk-adjusted net present value exceeding $400 million. Naturally, the achievable timeline varies by candidate, and may be longer in unexplored mechanisms targeting an unproven biological pathway in a disease area that is less well understood.
To achieve best-in-class timelines, companies usually front-load investments and run some processes in parallel rather than sequentially—steps that typically require them to recalibrate their risk tolerance. While some opportunities to accelerate preclinical development can be adopted as the standard operating model for all new drugs in future, others are specific to particular high-value projects, or subject to the probability of technical and regulatory success. To calibrate risk appropriately, organizations might consider their overall attitude to risk as well as the risk attached to the specific project under evaluation, bearing in mind such factors as the level of prior validation and the competitive intensity of the market being addressed.
Another key dimension in optimizing preclinical development is simplicity and transparency. Eliminating unnecessary complexity can improve value creation across the portfolio by reducing double work and other inefficiencies, enabling better management of resource capacity (such as the identification of upcoming resource bottlenecks), and cutting costs. In governance and internal review processes, for instance, reducing the number of stage gates and confining reviewers and decision makers to a small group of key people can help avoid inefficiencies, prevent rework, and free up resources. Companies can also benefit from implementing tactical measures such as setting clear rules for delegating tasks and blocking out time in the calendars of critical reviewers, to avoid delays.
In pursuit of simplicity, some companies replace standard open-tender procurement with a “preferred supplier” approach in which selected CDMOs (contract development and manufacturing organizations), CROs (contract research organizations), and other providers are engaged for multiple projects on prenegotiated terms. This reduces the number of steps and resources involved in contracting and helps build a trust-based relationship with partner organizations.
Pharma companies are sometimes concerned that accelerating or simplifying preclinical development could affect the quality of the scientific interrogation on which they depend to understand preclinical candidates, deliver a viable product, and achieve clinical success. However, with careful design, preclinical development can maintain or even improve quality and rigor while maintaining a rapid pace.
For instance, creating standards and templates for clinical development plans can help to reduce workloads, minimize human error, enhance quality, and improve speed. By tackling these plans at an early stage in preclinical development and introducing iterative feedback loops with key stakeholders, companies can anticipate and avoid capacity constraints and other bottlenecks. To prevent delays at key stage gates such as candidate selection, one company empowered teams to make decisions and provided them with clear criteria to ensure compliance with internal quality standards. Another company used automation to prefill tables in the investigator’s brochure template to reduce processing times while maintaining quality.
Optimizing preclinical development requires progressive thinking (such as questioning long-established processes), fresh ways of working (such as asking for cross-functional input early on), and a willingness to break new ground (such as entering into strategic partnerships). It also requires a readiness to adopt the latest technologies in the field, whether in chemistry, cell lines, or techniques. Successful companies are increasingly turning to digitization and automation to accelerate innovation, adopting machine learning and other forms of AI to enable in silico discovery and automating repetitive tasks such as pipetting. (See sidebar, “Digital and analytics use cases along the preclinical value chain.”)
What it takes to capture the value
For pharma companies seeking to optimize preclinical development, the best results come from acting on a combination of asset-level quick wins and portfolio-wide longer-term initiatives. Addressing areas one by one may be easier but prevents the capture of synergies between them, limiting the impact. Excellence in early development comes from coordinating cross-functional action on six fronts simultaneously: setting innovation and speed as the North Star, taking advantage of digital and analytics, setting up a future-ready delivery model, driving process innovation, ensuring nimble governance, and building agile talents and capabilities.
Set innovation and speed as the North Star
Committing to innovation and speed acts as a constant reminder of the mission: reaching FIH trials as quickly and effectively as possible while doing justice to the biological and mechanistic questions that arise during preclinical development, especially when exploring new mechanisms for molecules or new biological pathways. By maintaining a clear view of how functions work together along the critical path (a sequence of processes determining the minimum time needed) and regularly monitoring key metrics, companies can help ensure that innovations are properly implemented, operations run effectively, and delays are avoided or mitigated. For instance, one pharma company created a “cockpit” with dashboards displaying key metrics in preclinical development and beyond. The cockpit enables leaders to identify potential bottlenecks and issues before they arise and prioritize and sequence effective interventions.
Enable advanced insights with digital and analytics
When underpinned by the right data and tech infrastructure, digital and analytics can improve the quality and speed of preclinical development by enabling advanced data integration, automation, and the generation of cutting-edge insights. The use of AI in experiment design and molecule optimization can enhance and accelerate candidate nomination, for example, while the use of digital twins (as in silico analytical models) can improve prediction and validation decisions on pharmacokinetics, pharmacodynamics, efficacy, and toxicology during candidate selection. By embracing biotechnological and analytical advances (such as optofluidics and bioluminescence), companies can create digital platforms that allow them to make more rapid progress, reduce the number of validations needed, and optimize the use of technology.
Develop a future-ready delivery model
Such a model for preclinical development will need to take account of the critical decisions that the clinical organization has to consider in designing FIH studies, such as single or multiple ascending doses. Areas that don’t necessarily have to be on the critical path could still be optimized to free up time for high-quality thinking on experiment design and progression decisions. One pharma company reduced set-up times for FIH studies by developing a standard process for territory selection based on expedited regulatory pathways and data requirements. Other companies have found that established long-term trust-based partnerships with preferred CROs, CDMOs, and other suppliers in key territories can save time and effort by streamlining selection, contracting, and due-diligence processes.
Institute process innovation
Continuous process innovation is critical to improving the speed, quality, efficiency, and cost of preclinical development. Through a cross-functional approach involving preclinical sciences (such as drug metabolism, pharmacokinetics, and toxicology), technical development, process development, analytics, research science, and regulatory and clinical sciences, companies can often identify processes that could be completed more quickly. For instance, it can take months to move a material from drug substance to the product manufacturing suite if the process is governed by the same stringent procedures that apply to commercial manufacturing. If instead a company adopts phase-appropriate standard operating procedures for processes in late research and early development, it can balance robustness with the agility needed for rapid progress. The preparation of documents for filing for FIH studies is another area that can benefit from process innovation. If templates and pre-drafts are created for core regulatory documents such as the investigator’s brochure, teams can add new data as it is generated. Once the decision to file has been made, they need make only a few final refinements, enabling the documentation to be completed and submitted much more rapidly.
Continuous process innovation is critical to improving the speed, quality, efficiency, and cost of preclinical development.
Adopt nimble governance and agile project teams
Easing candidates’ passage through stage gates from candidate nomination to first-in-human with nimbler governance and agile asset teams can help flag bottlenecks and challenges at an early stage. Empowering asset teams and functional leaders to make decisions in line with predefined criteria can reduce the burden on internal governance and free senior executives to focus on strategic issues. One challenge teams commonly encounter is the need to make decisions on candidate progression and experimental design with incomplete information. Teams often wait for data points or experimental results that make no material difference to the eventual decision, when work could have proceeded with data collection continuing in parallel. To prevent unnecessary delay, teams can question whether more information is genuinely needed and consider how different outcomes might affect a decision. Leaders can set the right tone by showing how strategic thinking can be applied to the work of candidate teams.
Develop talent and core capabilities
Finally, excellence in preclinical development also depends on building talent and capabilities in core functions such as preclinical sciences, CMC (chemistry, manufacturing, and controls), and regulatory and clinical sciences. Training needs to go beyond functional skills to cover agile ways of working and cross-functional collaboration and decision making. Asset teams need to understand how to prioritize and sequence activities based on risk/benefit trade-offs. They also need to know which questions to ask, such as what impact a particular activity may have, how it might influence the critical path, and what incremental costs and risks it may incur.
Taking the first steps
Although each organization’s journey to preclinical excellence will be different depending on its particular structure, culture, and modality or disease focus, our industry experience suggests that the following steps can help any company get off to a good start.
Set a baseline and benchmark it
Creating a clear view of your baseline for preclinical development and benchmarking it against peers will help you understand your starting point. In defining the baseline for speed, typical metrics are time from candidate nomination to FIH trials or candidate nomination to proof of concept. Metrics for innovation are more qualitative—for instance, implementation of new capabilities in automation and digitalization. Baselining can be based on past performance or plans for a current asset. Either way, knowing where you are in relation to peers is critical in judging the opportunity and setting your ambition.
Develop a target blueprint and critical path
Based on the ambition and individual improvement opportunities you identify across functions, you can build a blueprint and critical path for following it. This is a complex collaborative effort that takes time and needs clear guidance from leaders, including a mandate allowing team members to explore all the optimization levers available across each of the areas of value and six routes for capturing it described earlier.
Pilot your new approach with priority assets
Starting with the areas of greatest opportunity, define and monitor clear metrics for success, such as the speed of achieving milestones. Monitor these metrics consistently, and capture lessons learned along the way to promote continuous improvement.
Apply lessons learned and scale
Build on the experiences of the pilot to scale the approach across your pipeline, building capabilities needed for long-term success, such as automation and digital and analytics.
Bringing new medicines to patients effectively and efficiently requires a dedicated effort focused on speed, simplicity, quality, and innovation. Pharma companies have achieved significant progress in optimizing clinical development to reduce time to launch and cost per asset, but untapped potential for improvement remains in preclinical development. Recent advances in technology, systems, and processes mean that now is the time to capture this opportunity.