Industries are continuously evolving, and the pharma industry is no exception. There are trends impacting the way we think about pharma, how pharma development is conducted, and the opportunities for pharma to make an impact on a societal level. Looking ahead, we can see a few trends that have emerged and that are gaining traction within the industry. This in turn influences how portfolio management is perceived and what it is expected to deliver.
The Case for Change
Pharma executives constantly make difficult strategic decisions pertaining to both assets and portfolios, and differences in the decisions taken can be worth billions of dollars. In today’s pharma environment, rapid and optimal decision-making is paramount as time translates not only to sales, but to patient outcomes. However, these decisions are made without consideration of salient uncertainties, inter-dependencies, and unforeseen down-stream effects.
For some time, drug development margins have been declining, forcing the pharma industry to reinvent itself. While improvement of efficiency has been necessary, this alone has not been enough. Many have transitioned into new organizational structures where strong organizational siloes have become more integrated around each compound, enabling development to become more patient-centric. Nevertheless, much of the industry remains tied to antiquated information structures that hinder intended progress in drug development. There is a significant need for a new type of solution that addresses three of the most prominent limitations in strategic decision making:
Reactive – Decision-making material that lays out possible futures often hide or even ignores risk. There are also clear limitations to answering ‘what-if’ scenario questions.
Slow – The static and siloed nature of organizational information flow leads to development delays, as decision material for a scenario can take weeks or even months to pull together.
Suboptimal – Departments often make strategic decisions without understanding the end-to-end consequences, making decisions suboptimal.
Next Generation Asset & Portfolio Management
New technologies including cloud computing, SaaS (Software as a Service), Big Data, and AI have allowed for new solutions that can significantly improve strategic decision making. Yet, few pharma companies have clearly expressed their specific needs, and even fewer vendors have addressed the limitations of asset and portfolio strategic decision making to facilitate optimal decision making. With technological advancements, equivalent advancements in asset and portfolio management are well overdue, and a new era within the field is emerging. Below are some of the key pillars of a next generation asset & portfolio management system. I. Seamlessly Manage Asset and Portfolios
Maximizing portfolio value requires the ability to seamlessly manage both the asset and portfolio level. Only then can the intricacies and value-driving factors of an asset be fine-tuned to fit the portfolio's overall constraints and risk. Next Generation managements systems should provide one fully integrated solution that accommodates capabilities to model, simulate, report, and analyze both individual assets as well as entire portfolios of assets. This will provide flexibility to combine a bottom-up and a top-down approach to portfolio management (e.g., robust analytics applied at the asset level can carry over to the portfolio). Users no longer need to toggle between different systems or manage several representations of the same information entity. The time to make supporting material available will be dramatically shortened as all necessary information and functionality can be housed in a single platform.
II. Cross-Functional & End-to-End Modeling
To gain a holistic understanding of an asset – its strategy, key activities, investment needs, value contributions, and uncertainties - you need the ability to capture knowledge that covers both the asset's development process and time on the market. The level of detail should not be fixed, but instead flexible enough to provide an overview, yet detailed enough to capture elements that affect the strategic decision making. This requires a flexible and highly capable modeling environment that incorporates instant simulation analysis as well as a collaborative environment for maintaining and tracing asset information.
III. Dynamic Modeling Using Inter-Dependencies
The development of an asset has a direct impact on its commercial success, and can further affect other assets within a portfolio. The commonly used static and siloed models neglect this dynamic, which leads to time-consuming updates and sub-optimization. The asset model for a next generation management system needs to be dynamic, so that the impact of a single assumption automatically flows through the model in entirety (e.g. a study delay in an asset automatically moves its launch date, its order-of-entry, peak sales, or even the start of a phase for another dependent asset). This enables team members from different business functions to instantly understand the overall effect of a change, which prevents sub-optimizations. This also increases the speed of well-informed decisions, from days or weeks to seconds or minutes.
IV. Flexible, Consistent and Efficient Asset Data Collection
Data that describe the future of an asset are often captured in different systems such as Excel, project management, or financial systems. This makes it difficult to share one consistent and holistic view of an asset or portfolio, which renders updates and analytics incredibly inefficient. A next generation management system should have the capability to serve as a data and collaboration hub for teams. Team members can quickly and easily get an updated view of an asset, trace, discuss changes, and get a shared understanding across business functions of an asset’s life cycle. Portfolio managers should be able to easily create input-form templates tied to underlying models that can be simulated and visualized. Data can be collected through manual input by team members or through automated import.
Once data has been input, users should be able to run simulations and get an array of outputs such as P&Ls, gantt charts, and decision trees from the same environment. Users should also have the ability to track all changes and see how each change affects the overall outcome. Asset teams thus have the incentive to continually maintain an asset forecast, enabling portfolio teams to have a real-time status view of the portfolio.
V. Embrace Uncertainty to Manage Risk and Opportunity
Risks and opportunities are always tied to uncertainty. However, if uncertainty is not expressed in asset models, risks and opportunities become hidden and limit the amount of information available to decision-makers. Thus, an asset model should allow for any illustration of uncertainty, whether it’s related to science, time, cost, or revenue. Next generation management systems should automatically apply statistical analysis or AI algorithms to this result, enabling decision-makers to get a probabilistic understanding of different outcomes and what constitutes significant risks and opportunities.
VI. Understand Historical and Future Data Changes and Trends
When effectively managing a portfolio or asset, it’s essential to understand changes over time, the underlying causes for these changes, and the impact they bestow. This requires a next generation management system to have robust data tracing. However, it’s equally essential to be able to move forward in time and assess the consequences of possible future scenarios, and further provide answers to portfolio scenario questions without having to step into individual assets. For individual assets, scenario questions are quickly answered through simulation filtering, decision trees, or simply by comparing the outcomes or different options.
Here are some examples of portfolio questions a next generation management system must be able to answer in real-time:
How would cost and revenue be affected if upcoming asset investment decisions turn out positive/negative?
What would it mean to our business if we could cut average phase 2 duration by 20% at a 10% cost increase?
What is the necessary input of research and licensing projects to reach our long-term goals?
The ability to answer these types of scenario questions allows for a more proactive mindset where possible proactive measures can be prototyped and assessed to mitigate risk or identify and strengthen opportunities.
VII. Boost Creativity Using Sandbox Environments
Reaching the optimal decision ultimately requires creative thinking where “crazy” ideas can be assessed and compared with more conventional ones in real-time. To allow for this creativity, an the system must ensure that:
Users do not need to worry about over-writing or harming existing information
Users can easily copy, prototype, evaluate, and compare different scenarios
Users alone can access their own environment and share findings with broader teams if and when they are ready
Thus, next generation management systems should offer sandbox environments where existing portfolios or assets can serve as starting points and into which explicit members can be given access for collaboration. These sandbox environments should be completely isolated from all other content. When options have been evaluated and crystalized, one should easily be able to move the designated content back into the "official environment."
VIII. Software as a Service (SaaS) for Continuous Improvement
The best way to deliver software today is by far through a multi-tenant Software as a Service model (SaaS). The advantages are overwhelming and include:
Continuous delivery – Bug fixes, updates, improvements, and new features are distributed instantly to all customers
High pace of development – As the vendor only has one code base to maintain, the speed of development is significantly higher, and customers can move faster
No IT maintenance – All hardware, maintenance, monitoring, security is remotely taken care of by the vendor
High-performance – Heavy simulations and advanced analytics performed can be performed in real-time by leveraging Cloud computing
Conclusions
The different departments involved in drug development need a collaborative environment to maintain a common, end to end understanding of individual assets as well as whole asset portfolios. Decisions need to be more proactive and more efficient, and the decision support needs to be in real time. Achieving this improvement and thereby getting the most out of each asset, requires not only new behaviors, but also a new type of tool that addresses current limitations. Captario has spent the last decade focused only on making this possible. We have put in place a solution that tenders to the above requirements, putting our customers at the very forefront of decision making in drug development assets and portfolios.