Safety surveillance during drug development is a globally recognized necessity. However, different regions and countries have different standards for what is required, leading to safety processes that need to be harmonized. This research analyzes the current regulations and seeks out solutions to increase the global viability of safety surveillance during drug development.

To read the full paper, click here.

UBC’s pharmacovigilance team excels at handling every aspect of your safety requirements at all stages of the drug lifecycle. Our commitment to Patients First has driven us to balance high-tech solutions with a personalized, experienced touch in our services. To learn more about UBC’s physician-driven pharmacovigilance offering, click here. To contact our team directly, click here.

The post Evaluating Existing Safety Surveillance Regulations for Drug Development appeared first on UBC.

The discussion included a group of experienced biopharmaceutical development professionals including epidemiologists, statisticians, and data scientists exploring essential considerations in generating evidence on the safety and efficacy/effectiveness of treatments using external comparator groups in the study design.

In this External Controls in Research Series, we will be exploring various topics such as the historical decisions of regulators in accepting results from studies using external comparators; what factors should be considered when selecting optimal data source(s) to identify patients for the comparator group; and the future of external comparators in drug development. Comparing outcomes of patients in an appropriate external comparator cohort with outcomes of the study population allows researchers to accelerate evidence generation and achieve a range of clinical development objectives.

What is an external comparator and how are these being used in research?

Let us first start with a review of definitions to establish context for the rest of our conversation.For our discussion today we are going to use the term “external comparator,” however you will also hear this concept being referred to as an “external control” or “synthetic control.” An external comparator is a cohort of patients, often assembled from real-world data sources outside of a prospective investigational study (such as a randomized, controlled trial), which is used to compare to a cohort of patients who participated in an investigational study. The external comparator cohort is designed to mimic as closely as possible the characteristics of the patient cohort from the investigational study to which it is being compared. Furthermore, because these external patients may come from real-world data, they typically are treated with standard-of-care therapies in usual clinical practice. The term “study population” will be used to refer to patients who have received the therapy under investigation.

In understanding why an external comparator might be selected instead of a traditional comparator such as placebo control or standard of care within a clinical trial, it is important to consider the limitations and challenges that can be associated with traditional comparators. For example, in life-threatening illnesses with limited or no treatment options, it may be considered unethical to conduct a study with a placebo control arm. In rare diseases, small patient populations and reluctance to enroll in randomized studies are factors that would impair the achievement of patient enrollment and sufficient statistical power in studies designed with traditional controls. For some rare diseases, patients may be eager to enroll in a study of a new investigational product thereby limiting the number of patients available for a comparator arm. In this situation, those patients remaining in a comparator arm may be very different in demographic characteristics and disease presentation, thereby introducing potential bias.

Furthermore, the digitization of healthcare data has created a rich landscape of high-quality healthcare databases. Taken in combination with recent technological advancements in data interoperability, we can now assemble highly customized external comparator data sets that contain the healthcare experience of patients with characteristics that closely replicate those of the study populations. These customized comparator datasets provide an efficient approach in clinical research settings that would have previously only used a traditional comparator.

In this second segment of our External Controls in Research Series, a virtual gathering of experts on the what, why, and how of external comparators in clinical research and post-marketing, we explore some examples of how external controls have been used successfully for regulatory submissions.

What are some examples of regulators accepting data generated from studies using external comparators?

According to Hatswell et al. (2016), between 1999 and 2014, the EMA approved 44 indications without randomized controlled trial results and the FDA approved 60 indications. Single-arm trials incorporating external control arms as the comparison group are becoming more commonly accepted evidence in both regulatory approvals and health technology assessments (HTA).

An illustrative example is a recently conducted single-arm trial of Blincyto® (blinatumomab, Amgen Inc.) that utilized an external comparator to demonstrate standard-of-care outcomes in patients with Philadelphia (Ph)-positive leukemia (Rambaldi 2020). Where the originally approved indication in 2014 was for Ph-negative precursor B-cell relapsed or refractory acute lymphoblastic leukemia (ALL), the 2018 accelerated FDA approval and 2019 EMA approval resulted in a label expansion to include both the Ph-positive variation as well (Pulte 2018). The external historical control group was derived from medical chart reviews of patients who received standard of care and used a weighted analysis of patient‐level data to establish effectiveness.

Bavencio® (avelumab, Merck KGA and Pfizer Inc), an IgG1 anti-PD-L1 antibody, received accelerated FDA and conditional EMA approval after comparison to historical controls for second line treatment of platinum-refractory locally advanced or metastatic urothelial carcinoma (mUC) (Baumfeld Andre 2019). In this example, the external controls were taken from a combination of an electronic healthcare database and a German cancer registry to establish the natural history of mUC.

We see drug developers using these approaches to accelerate research as detailed in the interview question above. Below are some select examples of recent FDA/EMA approvals which used external controls in the design of the studies provided as evidence:

Some common themes emerge from a review of this table:

• Regulators are more likely to accept the use of external control data when the disease is rare and/or the indication is for a disease with a high unmet medical need, so it is not surprising that the majority of these approvals/label expansions are for oncology indications.
•  The external controls came from a wide variety of sources: open label studies, historical controls from other randomized trials, and other secondary healthcare databases and chart reviews. This corroborates the general tenet of RWE described in a recent whitepaper from Duke-Margolis (Mahendraratnam Lederer et al, 2019) – that the data must be ‘fit for purpose’ and that there is no ‘perfect’ database to meet all external comparator needs; the right data must be chosen to address the particular research question at hand.

What are the critical factors that should be considered when selecting the optimal data source(s) for use as the external comparator?

Certain criteria for evaluating external comparison groups are more critical than others, depending on the data under consideration. Available data include (1) control or placebo arms from historical or ongoing clinical trials and (2) RWD that capture the healthcare experience of a defined population. RWD includes disease and product registries (both established and prospective) and routinely collected healthcare data, such as EMR and insurance claims. Additionally, for populations that require specialized clinical data for identification (e.g., evidence of a genetic mutation), chart reviews may be needed to provide the appropriate data elements for an external control arm (ECA). An overview of critical factors to consider when selecting appropriate data source(s) to create a scientifically valid ECA is provided below.

Considerations when using historical controls from randomized trials

Ideally, external control populations would come from the control arm of randomized clinical trials (RCTs) that meet the following: (1) address a similar research question, (2) have been conducted within several years and (3) have a similar study design and data capture process. Similarities and differences between the historical controls and the clinical trial target population should be evaluated to determine if the historical controls are appropriate for the research question. Relevant factors include:

• Disease criteria – changes in diagnostic criteria over time need to be considered.
• Study inclusion and exclusion criteria – determine if important subgroups were excluded from the potential historical control group. Were different thresholds or cutoffs used?
• Data collection process – frequency and timing of the capture of important variables such as exposure classification and outcome need to be considered. Sufficient length of follow-up may also be a concern.
• Clinical outcome definitions – determine if measurements of critical clinical endpoints are adequate to use as comparisons with clinical trial endpoints – e.g., a sufficient level of detail, similar coding for diagnoses. If patient-reported outcomes (PROs) are important to evaluate, were these captured in a similar manner?
• Covariate definitions – the capture of important variables required for control of confounding is important to review. Does the potential control dataset capture important covariates with the same level of granularity (e.g., concomitant medication use)?

Additionally, other factors that impact the appropriateness of a historical control database as a source for a comparator arm in a clinical trial are:

• Clinical trial design –An ECA is most commonly needed for single arm trials (SATs), where it may be unethical (e.g., life-threatening situations without alternative treatments) or unrealistic (e.g., rare diseases) to enroll patients into the standard of care (SOC) arm. Choosing an ECA for a SAT generally requires more rigor than when the ECA will serve as an additional comparator group for a traditional trial with existing controls.
• Size of final population – after imposing the exclusion criteria that mimic the clinical trial protocol, how many patients still qualify for the proposed ECA? Is this a sufficient sample size to test the study question, based on the study design?
• Standard of Care – biases in the types and patterns of treatment for the study indication in the historical control population need to be investigated, e.g., do the treatments represent the real-world clinical care experience of patients similar to those in the clinical trial, including dose and frequency of exposure.

Considerations when designing ECA using real-world observational data sources

• Incomplete data ascertainment– Information in observational data sources does not originate from “protocol-driven” care. This differs from data capture in historical control databases, where patients have pre-specified points of encounters with physicians or other medical staff to provide regular follow-up. Therefore, the potential exists for incomplete capture of critical study information in observational data, including change in exposure (e.g., SOC patient switches to or adds the target drug) or outcome identification (e.g., the occurrence of adverse events), leading to misclassification during the analysis.
• Data Quality – The quality assurance/control process of data used for RCTs, which often become part of regulatory submissions, has a very high degree of stringency. Regular oversight is maintained to ensure protocol specifications and visit schedules are met, and quality control checks are built into the data capture process. This high level of scrutiny is generally not associated with non-interventional data and could produce information bias when conducting analyses.

Finally, although patient characteristics may differ between the external data that are being evaluated as an ECA and the target population in the clinical trial, this does not necessarily eliminate the data as a source for an appropriate external control group. Through analytic adjustment methods (e.g., propensity score matching on key variables, subgroup, or sensitivity analyses) the external dataset may be adjusted to reduce or even eliminate the effect of confounding on the results. Researchers must recognize, however, that the number of covariates available for analytical adjustment will be limited by the number of relevant variables available both in the clinical trial data and in the external control database.

What are the essential methods and technologies needed to execute a study design involving an external control?

In the previous segment of our series, we considered the important factors for selecting the optimal data source to identify any one or more external comparator cohorts.  In this segment, we will explore the methods and technologies needed for assembling fit-for-purpose external comparator datasets.

External comparator cohorts are often assembled by combining a range of disparate data sources including secondary data collected through routine healthcare delivery and billing by payers (e.g., administrative pharmacy and medical claims databases, electronic medical records (EMR), laboratory data). Additionally, pooled data from historical control arms of completed randomized clinical trials (RCTs) and registries provide a valuable source for developing an appropriate comparator cohort.  These data exist in non-uniform formats with varying degrees of completeness and quality, particularly in the case of EMR data. This dynamic presents methodological challenges that must be overcome through a deep understanding of the dataset under consideration for developing an external control arm (ECA), and may require a robust gap analysis that will serve as the foundation for a common data model (CDM) from which regulatory grade outputs can be generated.

UBC’s advanced methods specialists and technology architectures are key to enabling data integration and harmonization.  The resulting CDM forges interoperability across disparate data sets and leverages best-in-class HIPAA compliant de-identification and matching to support longitudinal patient record linkage.  These are essential ingredients for enriching the completeness and quality of external comparators.

Standardizing Data into the Common Data Model 

Assembling disparate data into a CDM to enable analysis as an external comparator requires the combined expertise of data scientists, epidemiologists, and data warehouse specialists. Incoming data are normalized and mapped to the CDM based on industry-standard models such as Study Data Tabulation Model (SDTM) or Observational Medical Outcomes Partnership (OMOP). The process for standardizing data sources into the CDM is depicted below in the figure below.

Data Linkage 

The construction of an external comparator may entail the linkage of two or more datasets.  This complex process requires technical expertise to facilitate highly reliable patient identity mastering across these multiple data sources in a HIPAA compliant manner that does not require the exchange of PHI.   This process often referred to as “tokenization and linkage” requires expertise in complex domains such as Bayesian probabilistic matching, bloom filter hashing, and compliant use of hashed PHI fields.  

Once the optimal data are identified for the creation of the external control, researchers must apply advanced methods underpinned by a modern technology platform that is equipped to deliver fit-for-purpose datasets.  Please join us for the next segment where we will explore the important statistical analysis considerations for studies involving external control arms.

Are There Unique Statistical Approaches or Methodologies Required For the Analysis Plan When Constructing an External Control Arm?

To summarize the discussion up to this point, once the optimal data are selected for assembling the external control, it is essential that researchers apply advanced methods that are underpinned by a modern technology platform to deliver fit-for-purpose datasets. In the next segment of this series, we turn our focus toward statistical analysis methodology in the setting of external controls.

The experimental population and the external comparator population should be as similar as possible. The external control may be historical or contemporaneous. Historical controls may be based on published data or collected from medical records. Contemporaneous controls may be required for rare disease where recruiting adequate numbers to randomize treatment and control is not practical. However, most contemporaneous controls to date are captured retrospectively, i.e., charts are reviewed for a period of calendar time when the experimental population was observed.

The use of published data is problematic in that the characteristics of the control population and data capture are fixed (e.g., follow-up time for endpoint evaluation) and may limit design options in the experimental population. Historical controls using medical records and contemporaneous external controls provide flexibility in design to better match the experimental population and objectives of the experimental study.

There is a potential for bias and/or confounding effects resulting from the process of selecting subjects that qualified for the external comparator group or in how the data are collected. Care must be taken in the design of the study to make sure these biases are minimized. A few examples that may be applicable to some studies are:

• Chose endpoints that do not require extensive rater training as it is unlikely the raters for the experimental and control population will have the same level of training

• Consider an endpoint adjudication committee so that both sources are evaluated by the same group of subject area experts

• Design data collection timing to be similar to the experimental control to avoid differences in recall bias

When the populations are not exchangeable, methods such as stratification propensity score matching, or covariate modeling can be implemented to address potential confounding factors and differences in the populations.

Join us for our final segment where we recap strategies for external controls in research and conclude with predictions for the impact we foresee external controls having on the future of drug development.

Conclusion

The use of external control arms is an evolving area of regulatory interest in clinical research settings where a randomized, placebo-controlled trial may not be possible due to practical or ethical concerns (e.g., rare diseases). There are methodological considerations for the design and analysis of externally controlled trials to address validity issues and minimize bias resulting from a lack of comparability between the treatment and control arms. The FDA states in their most recent guidance for the use of external control arms (February 2023) that “The suitability of an externally controlled trial design warrants a case-by-case assessment.” Sponsors who are considering the use of an external control in an upcoming drug development program are advised to plan ahead by carefully reviewing recent detailed regulatory guidances and research papers on issues related to design, data sources, and analytic approaches. Additionally, communication with regulators should be established early in the clinical development process to determine whether this approach could be a suitable alternative to the traditional randomized trial for their specific product under investigation.

UBC’s epidemiologists, clinicians, and biostatisticians support the design and execution of modernized solutions that generate evidence on the safety and effectiveness of biopharmaceutical products. For more information get in touch with our team here.

REFERENCES

_{Baumfeld Andre E, Reynolds R, Caubel P, Azoulay L, Dreyer NA. Trial designs using real-world data: The changing landscape of the regulatory approval process. Pharmacoepidemiol Drug Saf. 2019. doi:10.1002/pds.4932}

_{Hatswell AJ, Baio G, Berlin JA, Irs A, Freemantle N. Regulatory approval of pharmaceuticals without a randomised controlled study: analysis of EMA and FDA approvals 1999-2014. BMJ Open. 2016;6(6):e011666. doi:10.1136/bmjopen-2016-011666}

_{Mahendraratnam Lederer, N., et al. Determining Real World Data’s Fitness for Use and the Role of Reliability. Duke-Margolis Center for Healthcare Policy. Sept 26, 2019. https://healthpolicy.duke.edu/publications/determining-real-world-datas-fitness-use-and-role-reliability. Accessed 11-3-2020.}

_{Pulte ED, Vallejo J, Przepiorka D, et al. FDA Supplemental Approval: Blinatumomab for Treatment of Relapsed and Refractory Precursor B-Cell Acute Lymphoblastic Leukemia. Oncologist. 2018;23(11):1366-1371. doi:10.1634/theoncologist.2018-0179}

_{Rambaldi A, Ribera JM, Kantarjian HM, et al. Blinatumomab compared with standard of care for the treatment of adult patients with relapsed/refractory Philadelphia chromosome-positive B-precursor acute lymphoblastic leukemia. Cancer. 2020;126(2):304-310. doi:10.1002/cncr.32558}

_{Seeger, JD, Kourney JD, Iannacone, MR et al.  Methods for External Control Groups for Single Arm Trials or Long-Term Uncontrolled Extensions to Randomized Clinical Trials. doi: 10.1002/pds.5141}

_{Thorlund K, Dron L, Park JH, Mills JM et al.  Synthetic and External Controls in Clinical Trials – A Primer for Researchers.  Clinical Epidemiology 2020:12 457–467}

_{Burcu M, Dreyer NA, Franklin JM, et al.  Real-world evidence to support regulatory decision-making for medicines: Considerations for external control arms.  doi: 10.1002/pds.4975}

_{Considerations for the Design and Conduct of Externally Controlled Trials for Drug and Biological Products
Guidance for Industry, 06 Feb 2023
https://www.fda.gov/regulatory-information/search-fda-guidance-documents/considerations-design-and-conduct-externally-controlled-trials-drug-and-biological-products}

_{Jaksa A, Louder A, Maksymiuk C, et al. A Comparison of Seven Oncology External Control Arm Case Studies: Critiques From Regulatory and Health Technology Assessment Agencies. Value Health. 2022;25(12):1967-1976. doi:10.1016/j.jval.2022.05.016}

_{Mishra-Kalyani PS, Amiri Kordestani L, Rivera DR, et al. External control arms in oncology: current use and future directions. Ann Oncol. 2022;33(4):376-383. doi:10.1016/j.annonc.2021.12.015}

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Using two different case definitions, this research tracked the number, characteristics, and outcomes of patients that were hospitalized with COVID-19. This highlights the discrepancies when counting COVID-19 cases with or without laboratory confirmation in the EHR. It also explores the variability in lab testing across different geography and demographics. Ultimately, tracking novel diseases using EHR needs to carefully consider case definitions since testing is more limited and diagnostic codes are still evolving.

You can read the full paper here.

To learn more about UBC’s expertise with real world healthcare databases and how this can benefit your clinical development and post-marketing research, get in touch with us here.

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This article discusses:

• Why integrating registries is necessary in the rare disease space
• The key data skills involved in building an integrated registry
• The technical requirements for building an integrated registry
• And more

To read the full article, click here.

To learn more about UBC’s observational research experience and capabilities, visit here or get in touch with us.

International Clinical Trials, May 2022, pages 58-60. © Samedan Ltd

The post Why Integrated Registries are Critical for Rare Disease appeared first on UBC.

This article about the development and future of real world data and its place in biopharmaceutical development covers:

• How data collection and analytics have changed in the last decade
• How RWD aided COVID-19 vaccine development
• What other innovations will emerge in clinical trials
• The future of vaccine trials
• And more

To read the full article, click here.

To learn more about UBC’s RWD experience and capabilities, visit here or get in touch with us.

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Every year, PharmaSUG brings together life science and health research professionals focused on the applications of technical solutions in data analytics and regulatory support. During the Real World Evidence/Big Data track, UBC was honored to present our approach to standardizing diverse laboratory data from electronic medical record databases.  Diversity in the naming conventions for laboratory tests and the reporting of laboratory results presents a significant challenge for generating meaningful real-world evidence to support healthcare decision-making. UBC’s Irene Cosmatos, Senior RWD Epidemiologist, and Michael Bulgrien, Senior Data Analytics Project Manager, developed the manuscript and associated presentation based on their many years of experience in designing, implementing, and evaluating real world evidence studies using global real-world databases. The manuscript was named Best Paper in this track.

The recorded presentation is below, and you can also access the abstract here.

UBC, a technology-forward company, is proud to receive this award that recognizes our contribution to the continuously growing but complex field of healthcare data informatics.  UBC’s multidisciplinary team of epidemiologists, database specialists, outcomes researchers, clinicians, and statisticians are always striving to improve the approaches to RWD evaluation that can generate valuable insights into disease understanding and improved patient care. To learn more about UBC’s approach to identify the right data for the right purpose and the leading technology infrastructure that powers our studies, head here.

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UBC’s Vice President of Global Products and Innovation Ron Lacy gave an exclusive interview about this award with Outsourcing Pharma. The interview discusses UBC, the innovative technology solution that led to this award, and how to combine scientific knowledge with practical operational and technological implementation.

“As a technology-forward company, UBC builds a culture of innovation. We encourage our product owners, operators, and software engineers to consider solutions that can be fit-for-purpose developed” says Lacy.

UBC is proud to receive this award for our innovation with mobile patient recruitment. We are always striving to innovate and better reach and serve patients wherever they are to enable more robust data and more actionable evidence. To start a discussion about our consultative, Patients First approach to clinical, safety, and commercial services, click here.

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Nicole Hebbert (SVP, Head of Patient Support Services, UBC), Jennifer Lim (Director of Patient Services, UBC), UBC partner SK Life Science and various industry experts spoke with PharmExcec.com about the impact a patient support program or ‘Hub’ can have on patients and prescribers during a pandemic.

Assets in Anxious Times: Patient Hubs Demonstrate Value During COVID-19 article explores in detail how a hub can ease patient access, drive patient engagement, and more effectively enable speed and efficiency to therapy through technology – even throughout a global pandemic.

In-person visits have drastically prohibited patients from visiting the site of care, whether from shelter-at-home mandates, office closures, or potential fear from patients exposing themselves to the virus, hub services can ease patient’s treatment anxiety and provide supplemental options to navigate their access.

During the COVID-19 pandemic, UBC has quickly and efficiently transitioned to a dynamic remote model without client interruptions. The team has supported three different launches since March across a broad range of indications from diabetes to epilepsy. Our in-home and telephonic nurse network has provided both clients and patients the peace of mind that care will not be interrupted, and the needs of patients will continue to be prioritized.

UBC’s patient support services can be customized to meet unique program and product objectives while addressing the needs and requirements of patients, caregivers, prescribers, pharmacists, payers, and regulators. UBC applies a holistic approach to the patient care continuum designed to maximize a product’s market penetration as well as its growth potential.

To get in touch with UBC to learn how we can provide patient support programs during COVID-19 and beyond, head here.

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Recently, Jersino Jean-Mary, Executive Director, European Late Stage Operations Team, and Aaron Berger, Executive Director, North American Late Stage Operations Team, shared their thoughts on how the pandemic is impacting clinical trials and post-approval research, and ways that the industry is working together to get patients the access they vitally need to novel therapies.

Traditional study designs are no longer practical due to the burdens on the healthcare system and restrictions in travel caused by the pandemic. What solutions are you incorporating into study designs that allow for data collection in this new paradigm?

Aaron Berger: A transformation was already occurring in the trial landscape and the global health crisis has accelerated this movement which touches most domains of study design and execution. From direct-to-patient digital recruitment strategies, patient-generated data collection technology, remote monitoring, and source document verification, telehealth-enabled study visits and in-home nursing visits, we are seeing widespread integration of these solutions into study designs across the drug development continuum.    

Jersino Jean-Mary: Our clients’ goals have always been to bring new therapies to market to ensure therapies reach patients and provide life-saving treatments as quickly as possible. The evolved clinical landscape we find ourselves in today provides an opportunity to reach patients more effectively and collect data utilizing technology to ease the burden on both patients and health care providers. The solutions we’re incorporating that include virtual study designs through remote / virtual monitoring, more efficient utilization of electronic medical records (EMRs), real-world evidence (RWE) data compilation, data warehousing, and registries, are driving efficiencies to shorten development timeframes for our clients. With our telehealth and in-home nursing services, we support our patients by easing their burden in adhering to therapies and ensuring higher patient compliance in data collection. These integral changes will be around for years to come.

How do you ensure good clinical practice (GCP) obligations are met for ongoing studies?

Berger: In late March, shortly after the outset of the health crisis, the FDA issued Guidance on Conduct of Clinical Trials of Medicinal Products during COVID-19 Public Health Emergency¹. This document was issued to provide guidance to sponsors in meeting their obligations to assure the safety of trial participants and maintain GCP compliance. The guidance document suggests that sponsors consider alternative methods for safety assessments, such as phone contacts, virtual study visits, and alternate site data collection. In addition, the guidance contemplates best practices for remote monitoring of data as well as electronic consent and signature processes. GCP obligations still need to be adhered to, but the delivery, safety, and monitoring of the study will need to be adapted.

Jean-Mary: General regulatory and protocol guidelines must be followed to ensure patient safety – regardless of how the study is adapted into the current landscape. We are still diligently training sites on study procedures/protocols and GCP, though we’re now training them more virtually utilizing electronic training platforms and local resources to effectively conduct virtual Site Initiation Visits (SIVs). In addition, we continue to closely monitor the activity and output of sites in adherence with GCP principles, again conducted virtually and utilizing fit-for-purpose technology. We have seen this change as an opportunity to employ a true risk-based monitoring approach, allowing for a more focused real-time data review and better assessment of data trends around protocol deviations, adverse events, missing data, quality of data. All of these could have a profound impact on the results of a given study.

What technologies do you use to ensure that you are conducting virtual monitoring in a compliant way?

Berger:  In the March Guidance, FDA provided specific options that would be considered acceptable to support the conduct of remote source document verification:

1. Sites can provide a “secure remote viewing portal that would permit site staff to provide access to the sites’ study documentation and/or trial participants’ source documents for study monitors review”.  We are finding that several of the site EMR platforms are enabling functionality that meets these requirements.
2. Site upload of certified copies of source records to a sponsor-controlled electronic or cloud-based repository contains appropriate security controls. We are deploying 21CRF compliant technologies that meet these standards.

By adopting these approaches, we closely replicate the conduct of the monitoring visit and conduct the essential function of source document verification in a virtual ‘data monitoring room’.  In addition, the virtual monitoring experience is further supported by video conferencing with Investigators and Study Coordinators, as well as a review of the eTMF, which was already widely adopted prior to the health crisis.  

Jean-Mary: Telecommunication technology enables our monitoring team and study staff to meet virtually to ensure sites are complying with protocol and study guidelines. In addition, our proprietary technologies, like our EDC platform, are tailored to support virtual monitoring. In combination with these platforms, we are able to review drug accountability, patient-informed consent, source documents in a virtual setting with technology platforms we have access to, as well as meet with Principle Investigators (PIs) and study staff. In-person monitoring may still have a place in the future of clinical studies; however, we see it with less frequency. Moving forward as an industry, we could take a more pragmatic approach to monitoring by implementing a true risk-based approach where there only a percentage of on-site monitoring sites are conducted annually, supplemented with virtual or remote monitoring as the standard. This would seem to be a more efficient option for consideration.

How do you recruit patients in a virtual setting?

Berger: Direct-to-patient recruitment strategies have been utilized for years, including advertising, social media, use of prescription claims and lab data to target patients. These tactics drive patients to a web-screener or call center for eligibility confirmation, telehealth-enabled PI interaction, and routing to an eConsent platform. A significant benefit to this approach is that the recruitment of patients is not restricted to the geographic areas that are within proximity to brick and mortar sites. This can be a significant advantage when conducting studies in rare diseases.

Jean-Mary: When recruiting for studies more virtually, it is even more important to ensure the visuals and tools utilized are clear, concise, easy-to-use, and engaging. It’s also key that the outreach is done via different modalities, through multiple channels, and directed to patients as well health care providers. We have produced more educational and recruitment materials, videos, and platforms for virtual trials which focus on providing several ways to pre-screen and enroll through multiple channels, such as text and web screeners. Call centers, mobile messaging, and digital assistant programs are also important for maintaining communication with potential and enrolled study participants. A key consideration is that all outreach is done in adherence to global data protection / privacy regulations, something that we have successfully navigated as communication is conducted more remotely.

How are you designing studies that rely less on the patient going to the site?

Berger: UBC has an existing virtual research, patient engagement, and in-home nursing platform that rapidly allows our clients to transform traditional clinical protocol into virtualized study designs. We understand how a pandemic impacts the ability to collect critical insights essential to successful studies. We educate our clients on solutions and strategies to incorporate remote and virtual technologies into their study design.

Jean-Mary: For several years, UBC has been lock-step with the evolution of the clinical landscape, focused on direct-to-patient outreach and leveraging technology to ease the burden on both patients and health care providers. This thinking was in place prior to the COVID-19 pandemic and we have just enhanced the implementation of our services in the design and conduct of our studies. At the subject level, we have increasingly implemented into study designs a variety of data collection services that incorporate a mix of home health nursing to perform lab sample collection, drug administration, and routine assessments, telehealth virtual study visits, patient-generated data collection (including ePRO / eCOA), as well as virtual assistant and text messaging platforms. At the site level, the design focus has been on minimizing the number of data collection timepoints on studies, incorporating a virtual monitoring model via telecommunication technology, and practical measures such as delaying on-site monitoring or conducting additional days on-site during windows where they are being allowed.

What strategies do you use to drive patient engagement and retention in a virtual or decentralized study design?

Berger: There are a variety of challenges in keeping patients enrolled and engaged throughout a study, and having a completely virtual trial comes with its own challenges. In order to mitigate patient drop-off and ensure adherence to trial timelines, we are utilizing mobile messaging platforms and virtual assistants to support the trial from start to finish. From eligibility, consent, scheduling, enrollment, education, and reminders, we are ensuring that the patient has the best possible experience in the study and is guided every step of the way through automated conversational intelligence.

Jean-Mary: Given the inherent challenges with engagement and retention in these times, UBC strongly believes that driving and maintaining interest starts with the simplification of study designs and their operational deployment. This includes streamlining data collection, providing effective training, disseminating engaging materials, and generally optimizing the study experience for participants. We also note that it’s vital to enhance the value of study participation for patients and health care providers. These include educational websites containing dynamic content and information, text/email engagement, and use of mobile app technologies. These involve having surveys and PROs completed remotely via patients’ own mobile devices or utilizing virtual assistant technology that travels with patients throughout study participation, providing reminders of things they need to do from a data collection standpoint to ensure quality data required for regulatory submission and review.

What are some of the key takeaways the industry should be thinking about moving forward in a virtual or decentralized study format as impacted by the current public health crisis?

Berger: Drug development is at an inflection point for disruption through the utilization of direct-to-patient and digital strategies that will modernize and accelerate the way we gather critical data and insights needed for regulatory decisions and beyond.

Jean-Mary: The technologies and strategies we just discussed from virtual monitoring to patient engagement are here to stay and are not just the future of research. UBC and the entire industry remain committed to accelerating research so our clients can continue to prove the safety, efficacy, and value of critical therapies to ensure treatment gets into the hands of patients in a more efficient manner.

The COVID-19 pandemic continues to cause major disruptions to the continuity of biopharmaceutical companies’ research and development efforts. From consulting on virtual or decentralized study design and execution, to independent and confident therapy administration, through post-marketing safety requirements, UBC is the full-service partner to help you overcome the challenges posed by the pandemic – regardless of where you are in the product development lifecycle.

To learn how to plan, prioritize and educate internal partners as you help your company enter the world of decentralized trials, download UBC’s Decentralized Research Playbook to uncover the key considerations today.

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UBC recently participated in a smallpox safety surveillance study. This prospective study included the enrollment of 20,136 subjects who were active-duty military personnel undergoing pre-deployment medical readiness. The trial was initiated to address safety concerns relating to myopericarditis.

Vaccine is the official journal of The Edward Jenner Society and The Japanese Society for Vaccinology. The literature article was published here on September 13, 2020, with contributions from the Naval Health Research Center, Sanofi Pasteur Inc, Emergent BioSolutions, the Department of Health Policy, Vanderbilt University School of Medicine, and UBC.

From conducting clinical trials to meeting post-approval regulatory requirements, we can help guide your infectious disease product or vaccine on its critical path to rapid approval and beyond. UBC’s leadership team have authored and supported countless submissions to regulatory authorities and remain current on the latest global regulatory trends and changes. To learn more about our experience and to discuss how we can support your clinical development, head here.

D. J. Faix, D. M. Gordon, L. N. Perry et al., Prospective safety surveillance study of ACAM2000 smallpox vaccine in deploying military personnel, Vaccine, https://doi.org/10.1016/j.vaccine.2020.09.037

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