Mastering bioanalytical project management

Cathy’s latest column discusses project management (PM) for the bioanalytical scientist, covering method building during the development phase, to the application of adaptive PM principles. Teams often land on a ‘hybrid’ approach, balancing structure with flexibility.

When I meet with fellow scientists who are interested in learning about career options for biologists or possibilities for a change from a lab-based role, opportunities in project management (PM) are often high up on folks’ lists. Indeed, in the bioanalytical space, there is a range of project management roles that are critical to the success of drug development and some common examples include:

• Coordinating sample logistics
• Managing internal program timelines at a CRO
• Providing clinical project management of sample collection kits
• Leading preclinical projects at a pharmaceutical company

For bioanalytical scientists whose roles do not have PM in the title, however, there are many opportunities to apply PM principles to the method development and validation environment. Since method validations follow (generally!) predictable steps, stages and timelines, traditional principles of the “waterfall” approach to PM are highly applicable, including the outlining of phases, planning of milestones and tracking of schedule and cost variances.

In contrast, while good method development involves the use of a project plan, the development of a brand-new method is often a non-linear process. For example, consider the development of a ligand-binding assay designed to measure the levels of anti-drug antibodies (ADAs) in patient samples. Initial method development work may assess the performance of a few basic designs — like the bridging format — for key parameters like assay sensitivity and drug tolerance. Then, downstream method development experiments may be iterative, adjusting and refining method specifics as parameters are optimized or as new patient populations or potential interferents are identified. This approach persists even when using design of experiment methodologies that simultaneously assess multiple parameters.

Examples of method building in the development phase

Below are several examples of how method building can be iterative in the development phase from a ligand-binding assay lens.

• Refinement of ADA methods as different purification and/or acid treatment steps are added to boost drug tolerance, thereby changing other method performance parameters
• Integration of target-binding antibodies to ADA assays, if target interference is observed
• Modification of the assay ULOQ and/or LLOQ based on precision and/or selectivity results in healthy or disease-state populations as the assay is assessed in development
• Changes to curve fit based on experimental results and data analysis
• Changes in incubation time or to buffer additives later in development to boost sensitivity or address a selectivity issue in a new patient population
• Changes to method parameters based on unfavorable observations about method robustness, performance across different lots of materials, etc.

The often cyclic nature of bioanalytical method development, therefore, can intersect well with principles of adaptive project management. While a full breakdown of adaptive principles and associated frameworks and tools is beyond the scope of this article, some of the key principles of this type of project management include the use of brief (i.e., a couple of weeks) iterative cycles of development, the integration of customer feedback, and some level of flexibility on overall product requirements [1].  This approach is typically associated with software development, but early bioanalytical method development shares key principles, including uncertainty, complexity and a need for stakeholder feedback.

Example: ADA method development by a CRO team

One good example of the intersection of these three overlapping elements might be the development of an ADA method by a CRO team for analyzing samples from a Sponsor’s trial with high expected serum drug concentrations. Some initial requirements are expected to be defined by regulatory guidance, such as an assay’s sensitivity to detect 100 ng/mL of ADA. However, as the performance of the custom materials is assessed and as preliminary cut points are determined, assay design decision making is likely to involve tradeoffs that require stakeholder feedback and/or iterative modifications to the method design: 

• Balancing higher sensitivity and higher drug tolerance
• Weighing up cost considerations against performance metrics
• Trading drug tolerance for robustness

Project management structures that incorporate opportunities for this regular feedback to be captured and then integrated into the method approach are likely to produce a stronger end product. Additionally, this approach can ensure that developers are compiling and prioritizing the features that will be of greatest value to the method, based on the Sponsor, study and regulatory needs.

More columns from Catherine Vrentas:

• The art and science of ADC bioanalysis: a storyboard approach to assay design
• The GLP mindset

Applying adaptive PM principles to bioanalytical development

Of course, not all principles of adaptive PM methodologies apply to laboratory assay development in the same way they might apply to software development. However, bioanalytical method developers can adopt some or many of the general principles of agile project management. As a first example, evaluation of method performance at each step of development allows for the communication of results to stakeholders and discussion about necessary changes. By waiting until the end of a highly structured method development process to assess key parameters, issues may indeed be discovered too late to avoid complete re-development.

Instead, adaptive approaches use multiple cycles of “design –> build –> test –> deploy” [2].

• Analyze/Design: A method developer can view a cycle as making a plan for adding an additional feature to the in-progress bioanalytical method, such as planning to add a target-binding antibody to the master mix of the assay based on results from the previous round of development testing
• Build: Create a new protocol that incorporates the planned change
• Test: Design and conduct an assay run that will elegantly test the impact of the method change
• Deploy: Communicate the impacts of the change to stakeholders and integrate the modifications into the updated method draft

Learning from Scrum methodology

As a second example, bioanalytical developers can benefit from certain principles of the (adaptive) methodology of Scrum [3]. At the beginning of each bundle of work, teams can review the highest priority end product requirements and ensure that they are being taken into consideration in the method design and testing. Brief “daily scrum” meetings allow the development team to coordinate and identify blocks to progress, whether it is a back-ordered reagent or a lack of resources. As the development team works to integrate features into the method (such as improving sensitivity or reducing matrix interference), regular client meetings are similar to “sprint reviews”, which are used to obtain customer feedback. Finally, the team can meet for retrospective meetings — “sprint retrospectives” in Scrum methodology — after each bundle of work to assess what is going well across the team, how the team worked through challenges, and how to improve processes and problem-solving for the future. Importantly, the use of some of these concepts does not imply that a full Scrum methodology is being deployed by a team, but rather by becoming familiar with diverse PM principles, bioanalytical scientists and team leaders can develop structures that work for the specific needs of their teams.

The hybrid approach: combining structure with flexibility

In practice, project management approaches often end up taking a hybrid approach, allowing the bioanalytical scientist to “combine the planning rigor of Waterfall with the flexibility of Agile” [4]. Structure is important in bioanalytical projects, including development work — monitoring timelines to ensure that methods are validated in time for analysis of critical samples, documenting data and rationale for decision-making, and preparing for handoffs between teams or phases to ensure a smooth project life cycle. Additionally, limitations on scope and budget are typically present in addition to the aforementioned timeline pressures and will necessarily constrain the extent of iteration and modification of requirements during method development. Waterfall principles/tools of contract modifications, change control and scope monitoring provide a backstop against large overruns in cost and schedule. Therefore, the benefits of viewing method development projects through an adaptive lens can be combined with traditional “waterfall” tools to create an excellent balance of the strengths and weaknesses of each approach.

Disclaimer: The opinions expressed are solely that of the authors and do not express the views or opinions of their employers, Bioanalysis Zone or Taylor & Francis Group.