Inherent Data Challenges of the Pharmaceutical Research and Development Process

While pharmaceutical research and development spending is expected to grow at a compounded annual growth rate (CAGR) of 2.8% through 2022, experts and stakeholders are seeing a downward trend in its return on investment (ROI). Pharmaceutical companies are under increasing pressure to either improve the success rates of their R&D or reduce their cost of failure, which a breakthrough typically would cover.

The pharma R&D process yields an average success rate of 4.9% from first toxicity dose to market approval. However, experts are questioning whether drug approvals had already reached their peak in 2015 and will continue to decline following the lower number FDA-approved drugs in 2016. With a bleak outlook on improving success rates for pharma R&D, more and more pharmaceutical companies are reducing their costs of failures through collaboration.

Since current internal R&D processes are losing financial viability due to lower success rates, increasing collaboration is the next stage in the evolution of pharmaceutical research and development. Pharmaceutical companies are forming public and private consortia with their peers and competitors, not only to share in the costs of failure, but also to try and improve success rates and get new drugs to patients faster. Pharmaceutical companies also form hubs and create collaborative networks of suppliers and other pharmaceutical companies. This setup allows them to focus on their core expertise such as clinical trial research, execution, and medicinal chemistry.

However, collaboration is not without challenges. Pharma R&D is an extensive process which requires recording, storing, and analyzing massive amounts of clinical data. Collaborating in the pharma R&D process multiplies these data challenges. To better understand these challenges, one has to first look at the pharmaceutical R&D process:

A Deeper Look Into the Pharmaceutical Research and Development Process

Pharmaceutical companies follow the Food and Drug Authority’s (FDA) five-step drug development process. This post will explore only the first three steps as they pertain to the research and development process, while the last two steps pertain to FDA’s approval and post-market safety monitoring.

Step #1: Discovery and Development

Researchers in pharmaceutical companies discover new drugs in a variety of ways. Researchers can dive deeper into a disease process, which allows them to design a product that can reverse or stop the progress of the disease. Researchers can also test compounds that can combat the effects of large numbers of diseases. Existing treatments which are not producing their desired effects or even harmful side effects are also opportunities for new drug discovery. At the end of this stage, researchers are provided with thousands of compounds which are candidates for drug development. Further testing conducted in this stage shortens the list of compounds for advanced study and development.

After identifying promising compounds for drug development, researchers conduct experiments to gather necessary information such as: how compounds are absorbed, distributed, metabolized and excreted, their optimal dosage, the best method for giving the drug (oral or injected), their toxicity, how they react to other drugs and compounds, their effectiveness, and their effects on different demographics.

Step #2: Preclinical Research

Preclinical testing ensures that developed drugs have no potential harmful effects and can be tested on people. During preclinical testing, researchers conduct studies to provide detailed information on toxicity levels and optimal dosages. While this step does not involve several stages, preclinical research is highly regulated by the FDA. In Part 58 of the Code of Federal Regulations Title 21 (CFR 21), FDA provides pharmaceutical companies with guidelines on good laboratory practices (GLP) for nonclinical studies.

Step #3: Clinical Research

Clinical research aims to determine how the drugs will interact with the human body. This step is also referred to as clinical trials. Typical clinical research consists of five stages:

Clinical Trial Design

This first stage in clinical research establishes a protocol or a plan for the trial. Researchers develop the questions they want answered by the trial, and also its objectives. They also define the study parameters such as the participation selection criteria, the desired number of people in the trial, the duration of the trial, the establishment of a control group, how drugs will be given to patients, how patients will be assessed, and what data will be collected, reviewed, and analyzed.

Investigative New Drug (IND) Process. 

In this stage, drug developers, sponsors, or pharmaceutical companies submit an IND application to the FDA before they begin clinical research. Sponsors indicate in the IND application the results of the animal study and toxicity data, their manufacturing information, protocols to be conducted, data from any prior clinical trials, and information about the sponsors.

FDA Approval

The FDA’s review team usually consists of specialists in different scientific fields. It often includes a project manager, a medical officer, a statistician, a pharmacologist, a pharmakineticist, a chemist, and a microbiologist. The review team assesses the IND submission of pharmaceutical companies to protect the volunteers participating in the clinical trials. After reviewing an IND application, the FDA review team can either approve the application so that the clinical trial can commence or disapprove of the application by ordering a hold order or stopping the investigation. Stopping the investigation is unusual. The FDA usually provides guidance on how to improve a clinical trial. A pharmaceutical company can revise its clinical trial design and submit a revised IND application. If the revised IND application meets Federal standards, the FDA can approve the application and the pharmaceutical company may begin the clinical trial.

Clinical Research Phase Studies

Consisting of three main phases, this stage tests for the safety and efficacy of the developed drugs on humans, as well as optimal dosage. Phase 1 involves testing the drug on 20 to 100 volunteers with the disease or condition. It aims to find out the optimal dosage to be given to patients and ensure the safety of the drug. Phase 2 involves testing the drug on up to several hundred volunteers with the disease or condition. It usually lasts several months up to two years as it tests the drug’s efficacy and possible side effects. Phase 3 involves testing the drug on 300 to 3,000 volunteers with the two-fold purpose of further testing the drug’s efficacy and monitoring for adverse reactions or side effects that surface only after one to four years of taking the drug. As an additional safety procedure, a fourth phase is conducted on several thousand volunteers to further test the efficacy and safety of the drug.

FDA Assistance

At any point in the clinical research phase, pharmaceutical companies can ask for help from the FDA. The FDA can assist pharmaceutical companies in reviewing their IND application prior to assessment, increasing its chances of approval. They can also help in designing large-scale Phase 3 studies which involves hundreds to thousands of volunteers. Finally, the FDA can enhance R&D processes by reviewing and interpreting guidance documents for pharmaceutical companies.

Once a pharmaceutical company or a drug developer gathers evidence that a drug is effective and safe through clinical research, it can then file a New Drug Application (NDA) with the FDA. If the drug passes the FDA’s review process, the FDA then works with the pharmaceutical company to develop the prescribing information, a process called labeling. A pharmaceutical company can then start marketing the drug through its marketing channels or through a distributor. In cases where the FDA does not approve of the application, FDA requires the developer to resolve remaining issues, answer additional questions, or conduct further studies.

The Data Challenges of Pharmaceutical Research, Development, and Collaboration

The pharma R&D process is long requiring years of research and data gathering. From discovery and development to clinical trial, a pharmaceutical company or drug developer will have gathered massive amounts of data on compounds, diseases, patient information, test results, experimentation results, formula, dosage, and FDA compliance requirements. These are kept in separate and disparate databases and consist of structured and unstructured information. First of all, it is a challenge for pharmaceutical companies to manage the volume, velocity, and variety of medical and clinical data.

Second, collaboration with other pharmaceutical companies, outsource partners, suppliers, distributors, and government agencies further complicates data management. With more players involved in the R&D process, pharmaceutical companies have to manage data sets coming from a larger number of databases inside and outside of their four walls.

Third, security risks are even higher with collaboration. Researchers and scientists or other collaborators require access to confidential information such as a patient’s personal health information (PHI) from clinical testing or health histories. This inherently increases the risks of critical information getting compromised as there are a greater number of data transfers and sharing.

Clinical Data Management: A Proven Solution for Pharmaceutical R&D Data Challenges

The accurate generation, gathering, and analysis of data are critical to the success of a clinical trial. Clinical Data Management (CDM) solutions help pharmaceutical and research companies to ensure the quality of their data. CDM solutions also help pharmaceutical companies secure and protect patient records and clinical trial participants’ data.

CDM delivers quality data and outcomes to pharmaceutical companies and other life sciences organizations. With a three-step process of collection, cleaning, and managing data, CDM gathers the maximum amount of data for analysis and ensures that the data is of the highest quality and integrity for statistical analysis by minimizing errors and instances of missing data.

Liaison’s ALLOY™ Platform for Healthcare offers pharmaceutical and other life sciences companies a comprehensive cloud-based CDM solution that provides streamlined integration and data mapping, improved data quality, and flexible data management. It is a scalable solution perfect for the massive amounts of complex pharma R&D data.

By partnering with Liaison Technologies, pharmaceutical and other life sciences organizations can ensure the high quality of their data, efficiently manage R&D and clinical trial data to accelerate time-to-market, and comply with industry regulations.

Are you looking for better ways to manage your research and clinical data?