Learn How Intelligent Data Brings Order to Decentralized Trials

Clinical trials play a vital role in bringing life-saving drugs and devices to market, and with them comes a plethora of documentation. The data is highly varied, comes from many different sources, and is challenging to find and organize. Life sciences and pharmaceutical companies need tools to automate the ingestion and submission process to navigate regulatory approval with ease and confidence.

Pre-pandemic, conventional trials were conducted in a centralized location. Hybrid clinical trials involve enrolling, monitoring, and collecting patient data from various locations, including pharmacies, labs, and even participant homes. In addition, clinical trial teams are grappling with massive volumes of other documents, including agendas, presentation materials, forms, approvals, changes, and summary documents requested when trying to bring new medications or devices to market.

According to Ernst & Young, “The interruption in clinical trials caused by COVID-19 has necessitated the acceleration of decentralization.”

As decentralized trials become the norm, pharmaceutical leaders benefit from automation in two areas of the clinical trial process. The first way to leverage automation is around data capture, and the second is when preparing submission-ready content for FDA consideration and approval.

Adlib’s document transformation platform enables life sciences and pharmaceutical companies to automatically process and assemble relevant clinical trial data into standardized, submission-ready PDFs. Read on to learn how automation will help your enterprise operate with greater efficiency and agility.

Comprehensive Data Capture

Decentralized trials mean pharmaceutical companies have even more unstructured documents and data to manage. The primary challenge in capturing required information is that it is typically scattered in multiple locations in hundreds of different file types, making document process automation even more complicated. As a result, pharma and life sciences enterprises are expending significant resources combing through large volumes of content manually, an inefficient process rife with errors and risk that hamper submission initiatives.

‍TMF Reference Model

 The Trial Master File (TMF) Reference Model is a guide that helps clinical trial teams identify the documents that go into a trial master file. The purpose of the TMF model is to drive consistency and compliance on clinical trial records to prepare for inspection and approval. Teams can search for essential information, classify, extract, and populate it to downstream systems with this knowledge. Since there is no single template available to prepare a submission for approval, the TMF Reference Model is a valuable tool to capture the correct information, mainly when wrestling with the large volumes of data associated with decentralized trials.

However, much of this effort today is being made manually. Automation takes the benefits of the TMF model to the next level. Submissions can be completed faster through automation, but automation also gives pharmaceutical companies confidence that no required piece of data is left behind.

Create Perfect Submissions Every Time

Submission requirements for the FDA, EMA, and other regulatory agencies may vary, including how the documents are formatted, their size, and how they are packaged. Being able to automatically assemble easily navigable PDF documents that meet the expectations of any governing body will enable pharmaceutical companies to get through any process with flying colors.

What complicates the packaging up of documents for FDA consideration is the location of the information and the myriad of file formats. Adlib’s document conversion software automatically transforms data captured from many sites involved in a decentralized trial into searchable, standardized, submission-ready PDFs, delivering vital application materials to the FDA in record time.

As a result, potentially life-saving drugs get to market faster, and everyone wins.

Notorious FDA Form 1572

Clinical trial leads responsible for submitting new medicines to the FDA are already familiar with Form 1572, ensuring compliance with the FDA Code of Federal Regulations. The purpose of the form is meant to help document a clinical trial. However, manually searching for and compiling data from hundreds of FDA 1572 forms—even more associated with decentralized trials—is a time-consuming burden.

An automated solution is the antidote to manual efforts and lost productivity. An AI model that looks for information required on form 1572 and automatically classifies and extracts the correct data means life sciences and pharmaceutical companies can stop extending deadlines and wasting valuable resources that could be spent performing higher-value tasks.

Automation and free-flowing data allow life sciences companies to be more efficient, innovative, and agile—simplifying the arduous FDA submission and approval process. 

The ultimate goal is to create fully compliant documents automatically to increase accuracy, reduce the risk associated with manual efforts, and accelerate FDA submissions and approval processes. With Adlib, pharmaceutical companies can be confident they are executing fully compliant documents automatically to sail through FDA submission and approval processes.

 The Final Verdict

In the highly competitive pharmaceutical industry, leaders must leverage technology to get ahead and stay there. Automation simplifies the front-end bulk ingestion of high volume, complex, and varied data, and it gives clinical trial teams the confidence to know their submission is being built at the highest level. Automation also plays a critical role in preparing submission-ready PDF documents to accelerate the final stage of getting a product to market. The Adlib platform‘s 20+ year track record has enabled pharma companies to automatically convert regulatory-compliant documents at scale into searchable, standardized PDF formats to navigate regulatory approval processes with confidence, accuracy, and ease.