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International Clinical Trials

Transparency Impact

Protocol transparency is becoming ever-more prominent in the pharmaceutical and biotechnology industries. The number as well as the type of data requirements needed for this transparency has dramatically increased over the past two decades.

Demand for greater protocol transparency began back in the early 1990s, when ClinicalTrials.gov required sponsors to publish high-level protocol data. One of the main objectives was to enable patients and researchers to search and select clinical trials for participation.

The next significant step was the introduction of the US Food and Drug Administration Amendments Act (FDAAA) in 2007. Sponsors were now obliged to publicise basic protocol results in addition to high-level protocol data. During this period, the focus of ClinicalTrials.gov shifted from informing the general public of protocol findings, to the scientific research community. The basic results section of ClinicalTrials.gov was just too complicated for the general public and patient population to interpret.

Disclosure Debate

The launch of global registries in other parts of the world continued to move forward while the disclosure community debated various aspects of the FDAAA over many years (such as the expected expansion by rule-making, which was to have been completed by 2010). Other discussions included the disclosure of financial data reported in clinical trials – for example, by the US Physician Payments Sunshine Act.

Currently, the industry continues to explore the automation and handling of the European Clinical Trials Database (EudraCT) results as the main respective topics. Pharma companies attending clinical conferences proudly present in-house developed solutions that have the capability to automatically post protocol disclosure results.

In a fairly typical IT adoption lifecycle, the vendor community offers a more efficient, cost-effective commercial solution to replace a plethora of in-house disclosure systems. Even after the protocol disclosure act, mandated by the FDAAA in 2007, pharmaceutical organisations still rely on in-house solutions to handle trial disclosure data. This seems to indicate that commercial solutions are unable to adequately provide the necessary efficiency and maturity needed by the industry.

Transparency Leap

The main focus today is the publishing of clinical trial data and the sharing of patient-level data. Over the past year, data transparency development has accelerated tremendously and is taking a quantum leap.

Publication of full clinical study reports and full study protocols are knocking at the door. Some companies have started making anonymised, patient-level raw data available on request to external researchers conducting their own analyses (1).

At the same time, enhanced clinical trials information for the general public is being optimised for patient trial participation. Sponsors will be required to publish protocol result summaries in layman’s terms and inform study participants of the trial results. Many initiatives are being launched to gain clarification and agreement on the type of proprietary data that can be disclosed, and how this can be achieved.

New regulations planned by various regulatory agencies are impacting the industry. The British Medical Journal and many other journals will only publish papers where the author has agreed on reasonable request to provide access to the patient-level data.

Research Trust

The benefits of extended data transparency are increasing the trust and source of truth in clinical research. Independent researchers can validate the published findings, and new insights can be generated as more researchers utilise the data from different sources. This helps to give answers to questions that might otherwise be difficult to provide. For example, hypotheses can be generated, giving fresh direction to future research, while maximisation of existing data lowers overall costs of global clinical research. In the end, patients will benefit from increased transparency and data sharing.

Extended data transparency benefits are not only limited to patients; the clinical research industry can also take advantage of increased protocol disclosure awareness and knowledge. Many hope this increase in demand for greater data transparency will improve the reputation of the pharma industry in society. The scientific knowledge generated by more extensive use of existing data posted on clinical trials will also enable the industry to make better investment decisions in the R&D area.

Patient-Level Drawbacks

There are clearly many advantages in posting patient-level data to increase trial transparency. Despite this, there are a few implications to consider when posting data on trial participants.

In general, data contributors may not be willing to open patient-level data for the general public for clinical trial exploration. This could inhibit patient recruitment rates for the trial, increasing costs and timelines for the study. Patients participating in such trials will need to complete a consent form to protect their confidentiality, while allowing their information to be used for general research and external stakeholders. Even then, institutional review boards might not approve this level of data disclosure.

Patient-level data is anonymised data that could be combined with other datasets, which could enable patient de-identification. Data contributors need to ensure the patient-level data is formatted correctly in order to protect the participant’s confidentiality, while allowing the information to be used for general research. None of this is simple to achieve in an era where there is a growing fear of re-identifi cation. Once this sensitive data is made available to external researchers, the pharma industry and the healthcare sector may not have full control of the data.

Risk and Concern

There is a risk and concern of companies using highly confidential, patient-level data to centre their business model around, along with creating patient profiles to increase patient recruitment. Obviously these companies are less concerned about patient confi dentiality and privacy issues. The result of this lack of respect for patient confidentiality could have a negative impact on recruitment rates. Recent news suggests that a considerable segment of WhatsApp users have moved to more secure apps after the takeover from Facebook was announced (2). This example demonstrates how sensitive people can be when it comes to their data privacy.

As a result of more demanding trial transparency requirements, commercially confidential information (CCI) will be published meeting earlier timelines. The European Medicines Agency (EMA) states that “clinical trial data cannot be considered CCI as the interests of public health outweigh considerations of CCI” (3). For the EMA, CCI considerations are second priority when it comes to clinical trials; if patents need to be filed earlier, they will also expire earlier. This will have a negative impact on revenues generated from successful drug developments.

Junk Science

In addition, some people are afraid of ‘junk science’, a term used when science produces irrelevant results. Statistical departments within pharma companies have high expectations and scientific rigour to adhere to. They expect external clinical researchers to meet the standards. These expectations can, in many instances, turn out to be unrealistic. An external researcher may only be interested in a very specific question, and may not run such analysis on a day-to-day basis. Therefore, certain expected standards, resources and processes may not be in place that are typically found in the statistical departments of pharmaceutical companies and contract research organisations (CROs).

The best protection against junk science is ensuring greater trial transparency and accuracy. This makes it easier for the general public and scientific researchers to provide counter-evidence against inaccurate data postings. It ensures integrity of the trial data published, and reduces the risk of individuals losing credibility and reputation in the clinical research industry.

Patient Expectations

The pharma industry and trade associations are discussing and committing to the sharing of trial data results with patients who participate in clinical trials (4). Sharing positive clinical trial results poses a challenge, versus sharing negative trial results (5,6). Companies submit proposals and agreements with regulatory agencies for approval about the wording and intent of the information given to the patients in order to avoid any kind of pre-approval promotion. The main concern is how to control the positive results published and, in turn, manage the expectations of the patient community.

Assume a Phase 2 trial shows promising results for a serious disease. Given that patients are well-informed of the clinical trial results and are savvy users of social media, there is a high probability this news will spread swiftly around the interconnected patient community, even if a non-disclosure agreement is signed by the patient. How do doctors and trial investigators quickly explain to the patient community that, despite the positive results posted, this is just a Phase 2 trial, and that multiple Phase 3 trials still need to be conducted (which is likely to take a number of years before they can get a positive outcome, and before the product can be made available to patients)? What can we do to support the doctors – not just the investigators – with communication to patients?

We could argue that this issue already exists since results are publicly available on the websites of ClinicalTrials.gov and PharmNet.Bund. However, there is a clear difference in publishing results in a format difficult to read for the layman, and communicating directly to patients in jargonfree language. This is not to say we should not inform the participating patients, but ways need to be found to address patient expectations.

At the same time, we need to consider the claims of pressure groups that ask for retrospective disclosure, for regulators and journal publishers to put more pressure on compliance with existing requirements, and for the widespread sharing of full trial datasets for all studies. The assumption is that such disclosure would allow independent scrutiny of trial data to enable physicians to make fully informed decisions on the efficacy and safety of treatments (5,6).

The Future of Disclosure

What will come next? With the publication of full study reports and access to patient-level data, there seems to be a natural end for increased transparency in the clinical research industry. What else could be published? What about patient safety and effi cacy? There are many factors assessed when evaluating criteria for drug safety and efficacy (5,6). This important safety criterion is also considered in preclinical trials. Will trial transparency be needed in preclinical trials before clinical development occurs in human research? Will we see requests to publish complete pharmacological and toxicology trial results in this decade?

Let us also consider marketing – obviously a different topic of discussion concerning trial transparency. This is another direction for debate that trial transparency could take in the near future. Large pharma companies often spend more money on sales and marketing activities than on R&D. Considering the level of focus on trial data transparency, marketing activities might very well be the next area to target in the clinical research industry.

References
1. Ekelenburg J, Sharing isn’t easy – sharing anonymised patient-level data and clinical study report disclosure, CBI Clinical Data Disclosure, January 2014
2. WhatsApp with WhatsApp? Huffington Post. Visit: www.huffingtonpost.com/mark-weinstein/whatsapp-withwhatsapp_ b_4856338.html
3. Publication and access to clinical-trial data, EMA. Visit www.ema.europa.eu/docs/en_GB/document_library/Other/2013/06/WC500144730.pdf
4. Principles for responsible clinical trial data sharing developed by Efpia and Pharma. Visit www.phrma.org/sites/default/files/pdf/PhRMAprinciplesforresponsibleclinicaltrialdatasharing.pdf
5. Goldacre B, Bad pharma, ACDM Annual Meeting, 2014
6. O’Brien S, Openness in clinical research, ACDM Annual Meeting, 2014



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Mathias Poensgen is Product Manager and a subject matter expert at ArisGlobal. He has spent more than ten years in the pharma industry in various leading positions in clinical operations, project management, business process management and clinical IT. Mathias has led eClinical programs, re-engineering projects involving clinical operations and data management, and established a successful benchmarking and performance management process. He holds Master’s and PhD degrees in Physics.

Jessica Schell is a Clinical Solutions Engineer at ArisGlobal. With 15 years in the industry, Jessica has gained experience in leading clinical project managers and teams from Phase 1-4 and late-stage clinical trials with various therapeutic indications, as well as leading the implementation and design for client data integration services. She continues to establish key relationships with clients and partners to ensure a harmonised approach using eClinical solutions.

Simon Wilson
is Head of Clinical Program Management and Training, and a Clinical Operations and Data Management subject matter expert at ArisGlobal. He started his career in clinical research at a site and lab level before progressing though data management, clinical operations, clinical technology and process implementation leadership posts at Bayer, PAREXEL and CSL. Over 15 years of experience in head offi ce and affi liate pharma and CRO settings have provided him with a thorough understanding of this topic.
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Mathias Poensgen
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Jessica Schell
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Simon Wilson
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