Discovering and developing new drugs/ medicines is very crucial for the
pharmaceutical industry. The increasing number of drugs approved in recent years
demonstrates the impact of modern drug discovery approaches, digital technologies,
and automated drug development methodologies. Drug development is a systematic
and methodological process of developing a new pharmaceutical drug once the process
of Drug discovery has identified the prime pharmacological component. The structured
sequence of steps followed for drug development aims to ensure the safety and efficacy
of the drug being developed. It includes pre-clinical research on microorganisms and
animals, preparation of detailed data with respect to pharmacology, pharmacokinetics
and toxicology details, application and approval by regulatory authorities and
conduction of clinical trials. The conduction of clinical trials is an expensive affair as it
needs a collaborative effort by multiple stakeholders along with a high level of
monitoring and regulation. The data generated during the lifecycle of clinical trials is
very critical for pharmacological scientific publications, regulatory approval for the
target drug and post-marketing surveillance that ultimately leads to the development of
better decision support systems for drug development. Hence, the data integrity of such
data is of prime importance. Several Clinical data management (CDM) systems have
been developed to ensure seamless collection and management of clinical trial data.
These CDM systems enable useful analysis and decisions supported by authentic data.
However, such systems face several security challenges with respect to privacy,
integrity and authenticity of the clinical data. Another major challenge in conducting
the clinical trials is finding the appropriate willing candidate who is physically and
clinically suitable for the study. In view of the above, it is highly desirable to have a
technology component that can address the above-mentioned issues. In this chapter, the
technologies like blockchain and cloud computing have been introduced to address the
challenges posed by clinical trial data management. The paper also proposes a
blockchain based secure clinical data management system. The proposed system
intends to help the data security issues like data integrity, privacy, ease and quick
access to immutable clinical trial data with thorough access control enabling greater
transparency and accountability.
Keywords: Blockchain, Clinical trials, Clinical data management, Cloud computing, Drug development, Data integrity, Security, Smart contracts.
