April 22, 2015

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Critical Points when going from Data Conservative' to the Open Access World

Why open data and crowdsourcing approaches are critical in today’s world?

In today’s increasingly connected and collaborative world, advancements in science cannot be done behind closed doors and in silos. Especially it is important for the big pharmaceutical companies where they are going through a phase of dwindling R&D pipelines and also an ever increasing demand for new drugs. Hence there is a greater need for continued and accelerated development of new therapies along with their speedy approvals. Pharma companies are in a dilemma – faced with a multi- forked problem – on one hand there is a need to strike a balance between the demand and supply of new drugs, on the other hand manage the increasing pressure to curb the rising R&D expenditure, increase affordability by reducing the price of drugs, improvise on patient safety and improve their efficiency metrics of R&D i.e. how many potential drug candidates finally come to the market and how soon. But is this steep increase in R&D costs and the static rate of drug approvals, affecting just the pharma alone? No, it isn’t – the burden has to be borne by all – all stakeholders including patients who are a part of the global healthcare community.

To tackle this plethora of problems the recent trends show a surge in collaborations amongst various stakeholders of the pharma industry with a focus on reducing the duplication of efforts, harnessing the collective insights and expertise gathered from these collaborative activities as well as testing new ideas for the betterment of the drug discovery and development process while also improving on patient safety, outcome and data quality aspects. In this context, one of the key areas of focus is on cross organization (pharma, researchers, patients, regulators, technology providers etc.) collaborations around data sharing and data transparency.

Pharmaceutical companies should be able to share information on elements under their study protocols, compound libraries, study designs and statistical analysis methodologies, trial processes and results, relevant patient data, manufacturing techniques etc.

 Critical points to consider while undertaking an initiative of data sharing and transparency

To bring in real value & collaborative success and also to realize the cost-benefit, the data sharing exercise should be carefully and meticulously planned. So before an organization decides to undertake an initiative on data sharing and transparency, they should consider the following points

  1. Decide on the kind of information/data and the quantum of the data that can be shared with others
  2. Decide on whom to share the data with and the intended use of the shared data
  3. Decide on processes and methods to address patient confidentiality, regulatory compliance and data privacy aspects
  4. Implement data de-identification standards (currently the industry is still in the process of defining the rules that need to be applied for data de-identification) 
  5. Implement proper access controls and review mechanisms around internal data sharing guidelines
  6. Secure transmission of data into the target data repositories
  7. Ensure that the data shared is used in a secure manner in accordance with the data sharing and usage agreement i.e.  – intended users should be using the data, establish a traceability matrix of the data shared etc.

The debate on trial transparency and data sharing has not been new and so are the initiatives around it. Few pioneering initiatives to push this ‘open-access movement’ have been through the efforts of the Cochrane collaboration, PhRMA, EFPIA, C-Path Institute, ClinicalTrials.gov site for study results, Yale University Open Data Access, AllTrials, Transcelerate, Project Data Sphere for oncology trials historical control data, Lilly Ventures, GSK’s DPAc - Discovery Partnerships with Academia, Janssen Research and Development, etc. Data sharing has come a long way from the initial efforts of sharing just the trial summaries to now being able to do pooled analysis across trials and sponsors, to even getting access to the individual subject level data. It is predicted that the open data/open access movement will see increasing focus as more and more organizations are expected to come forward to be part of these initiatives.