The COVID-19 pandemic interrupted pharmaceutical and medical device development in many different ways. Travel restrictions, subject illness and staff shortages at investigational sites resulted in delays in site start-up, subject and monitoring visits. Missed subject visits also resulted in increased amounts of missing data and lower data quality. Ultimately, all this had a major impact on sponsors as well as patients awaiting treatments. Employees at Abond CRO were uniquely trained and skilled to provide sponsors with the most efficient tactical and strategic approaches to address these new challenges, as described in this article. We are also very familiar with, and strictly adhere to the FDA COVID-19 related guidance.

Efficient Tactical Approaches during Pandemics

Every Abond CRO department was affected by COVID-19. We used our agile processes and technical expertise to navigate the complexities of the pandemic.

Clinical Operations

Most meetings that focused on the conduct of clinical studies have historically involved personal contact between sponsors, sites or subjects. These contacts had the effect of building teamwork and trust between all parties. During the COVID-19 Pandemic Abond CRO merged the use of new tools with the historical personal touch approach in order to keep studies on schedule during the travel restrictions of the pandemic.

Investigator Meetings are very important at the start of a study to ensure understanding of the protocol, procedures and safety concerns associated with the research. Abond CRO still finds these meetings valuable, however the team recognized the importance of following the CDC guidance to avoid unnecessary travel. Thus, the team held Investigator Meetings remotely while still achieving the traditional benefits of in-person events.

Monitoring of studies has traditionally been in person although the pandemic has caused many studies to shift to a remote style with mixed feedback from the sites. At Abond CRO we worked with the sponsors and the sites to tailor a set of tools and visit activities to ensure the safety and data integrity of the study while respecting the operational needs of the site. The assigned clinical research associate adopted site established systems for source data verification and drug accountability, however if the site did not have a remote method, the Abond CRO team either performed a traditional in-person visit or deployed easy-to-use source verification and electronic investigator site file systems on a site-by-site basis. The use of these systems in combination with video conference calls proved to be effective and less disruptive to the sites during monitoring visits.

Data Management

Due to the aforementioned staffing shortages caused by the pandemic, it was essential to lessen the burden on investigational sites as much as possible. One tactic to do this was to ensure each study had a well-built electronic data capture database that was in production prior to site initiation to allow site personnel to be properly trained prior to screening their first subjects. In addition, Abond CRO Lead Data Managers guided the clinical study team to ensure that the database was collecting data required per the protocol, rather than “nice-to-haves” that can lead to frustration and increase the risk of burnout at the sites. It was also vitally important that, whenever possible, the database fired queries immediately upon submission of the electronic case report forms (eCRFs) to decrease the need for study coordinators to have to revisit long past visits, along with all the source data associated with those visits.

Biostatistics and Programming

With full knowledge of regulatory guidance documents [1, 2], the Abond CRO Statistics team was able to adjust swiftly to detect and assess any impact to study data due to the COVID pandemic. Particularly, consideration was given to any statistical analysis plan (SAP) amendments and amended/additional statistical outputs by considering what endpoints were likely affected by COVID-19 and thus could impact treatment effects with particular focus on the primary and key secondary endpoints. For example, we communicated with project management for insight into project continuity at sites and with data management to review any new eCRFs and for potential insight into the volume of missing data to determine the appropriateness of missing data handling procedures. We also considered what additional sensitivity analyses might be required and the impacts to intercurrent events, sample size, and any planned interim analyses. Our teams expeditiously brought forward our assessments and recommendations for discussion with our clients to address any COVID-19 impact detected in statistics and programming.

In the early stages of the pandemic, following updates within data management and statistics, the Abond CRO programming group reacted quickly to the influx of database and statistical updates that resulted from assessments of COVID-19 impact. Program updates were already underway when CDISC (Clinical Data Interchange Standards Consortium) released the Guidance [3] to account for additional data captured. This additional information was incorporated within SDTM (Study Data Tabulation Model) and ADaM (analysis data model) datasets. Dataset documentation, including reviewer’s guides, were tailored to carefully define the inclusion of COVID-19 related data.

The increased programming effort carried through to the outputs, as revised in the SAPs. We reacted by programming the additional sensitivity/subgroup analyses, listings, etc. In some cases, the number of outputs increased more than 20% over originally planned. In spite of changing timelines, changing databases, increasing deliverables, Abond CRO programming was able to meet all output delivery timelines.

Medical Writing

Medical Writing faced new challenges during COVID-19. Any amendment to the study protocol and any decision taken because of COVID-19 recorded in the trial master file was required to be included in the CSR. The medical writer also assured that clinical study reports described, in the appropriate sections of the report, any contingency measures implemented to manage study conduct during disruption of the study that was a result of COVID-19 control measures, a listing of all subjects affected by the COVID-19 related study disruption, and any analyses that addressed the impact of implemented contingency measures (e.g., subject discontinuation from investigational product and/or study) on the safety and efficacy results reported for the study, based on the guidelines published by the FDA [2].

Efficient Strategies for Product Development IN Pandemics

Moving forward, we must recognize that efficiency in medical product development is particularly important when dealing with serious diseases, when resources are scarce and the number of patients is limited, or under extraordinary circumstances, such as pandemics. Efficiency can be maximized by implementing the following optimal decision concepts.

Avoid Conducting Unnecessary Trials

The first question with optimal decision-making should be, which trials are necessary for development, in order to avoid conducting unnecessary trials. The most common example of an unnecessary trial is when a sponsor conducts a Phase 2 trial only to make a decision on  whether the product should proceed into Phase 3 stage of development. This can be handled much more efficiently by skipping that Phase 2 trial and making the decision at an interim analysis in the Phase 3 trial itself. Another example is when the sponsor has to decide on the dose, subpopulation, or the primary endpoint for the confirmatory trial. A common approach is to address this question in a separate Phase 2 trial. Seamless [4] and informational designs [5] allow making decisions within the confirmatory trial itself. Finally, the sponsor should explore when the use of external data is appropriate [6]. In pediatric product development, extrapolation of adult data can sometimes be acceptable to the FDA [7].

Optimal Sample Size

A second issue to consider is if trials are appropriately powered. The improvement in probability of success (PoS) of a clinical trial is largest with smaller sample sizes. It gradually becomes smaller and smaller until it eventually levels off. Impact of overpowering clinical trials cannot be assessed within the trial itself. Making this decision in a broader context is of particular importance, as spending more resources on one drug will impede the development of another [8, 9]. More efficient designs would allow studying more treatments w the same budget.


  1. United States Food and Drug Administration. Statistical considerations for clinical trials during the COVID-19 public health emergency. Guidance for Industry. June 2020.
  2. United States Food and Drug Administration. Conduct of clinical trials of medical products during the COVID-19 public health emergency. Guidance for Industry, Investigators, and Institutional Review Boards. March 2020 (updated on August 30, 2021).
  3. Clinical Data Interchange Standards Consortium: Guidance for Ongoing Studies Disrupted by COVID-19 Pandemic. April 2020.
  4. Chaturvedi, PR Antonijevic Z, Mehta C. Practical considerations for a two-stage confirmatory adaptive clinical trial design and its implementation: ADVENT Trial. In He W, Pinheiro J, Kuznetsova OM (Eds.). Practical Considerations for Adaptive Trial Design and Implementation. Springer New York 2014 (pp 383-411).
  5. Beckman RA, Chen C. Informational designs and potential applications to rare disease. In Carini C, Fidock M,Gool AV (Eds).Handbook of Biomarkers and Precision Medicine, , Chapman & Hall/CRC, 2019 (pp 183-188).
  6. Ghadessi M, Tang R, Zhou J, Liu R, Wang C, Toyoizumi K, et al. A roadmap to using historical controls in clinical trials – by Drug Information Association Adaptive Design Scientific Working Group (DIA-ADSWG). Orphanet J Rare Dis 2020;15: 69.
  7. Dunne J, Rodriguez WJ, Murphy DM, Beasley NB, Burckart GJ, Filie JD et al. Extrapolation of adult data and other data in pediatric drug-development programs. Pediatrics 2011 :128(5):e1242-9.
  8. Antonijevic Z. Impact of adaptive design on pharmaceutical portfolio optimization. Therapeutic Innovation & Regulatory Science 2016;50( 5): 615-9.
  9. Chen C, Beckman RA. Optimal cost-effective designs of phase II proof of concept trials and associated Go-No Go decisions. J Biopharm Stat. 2009 19(3):424-36.