"Next Generation" Drug Development Strategies

Introduction

Asia Pacific’s biotech companies are increasingly challenged to stay agile in their drug development process while ensuring patient centricity. Innovative trial design is an important strategy for these companies to stay ahead. From screening master protocols to the use of data science and artificial intelligence (AI), how can biotech companies achieve the best patient outcomes? Here are three considerations for companies when planning drug development strategies.

Adopting the right master protocol

A master protocol is a unifying and efficient study design that evaluates multiple treatments, combinations, indications, or patient cohorts within a single trial. There are different types of master protocols such as the basket trial, the umbrella trial and the platform trial. In Asia Pacific, biotech companies are leaning towards the use of basket trials as sequential testing can be avoided and efficiency is possible.

With different types of trial designs, biotech companies need to consider the balance of science and operational efficiency when picking the right master protocol that would ultimately improve patient care and outcomes.

At IQVIA Biotech, we employ a consultative framework that lists the considerations used to help decide if a master protocol or individual trials is appropriate:

Is there a similar inclusion and exclusion criteria for the protocols?
Can a single screening protocol branch off into multiple arms?
Do the arms of the master protocol overlap during data collection?
Are there shared endpoints across the arms, or does each arm has its own endpoints?
How many parties are involved and are they able to have the appropriate governance framework?
Are the arms and all the parties involved on the same timeline?

This framework helps biotech companies in Asia Pacific who are adopting master protocols, beyond oncology-related trials to other therapeutic areas, plan ahead.

Usage of Machine Learning (ML) and Artificial Intelligence (AI)

AI and ML can be used to design more efficient and effective clinical trials and synthesize arms of trials. Companies can leverage multiomic data and algorithms that are based on a wide range of data sets such as historical clinical trials, real-world data and molecular data, to observe the responses of digital patients and improve trial outcomes.

AI and ML can also hone the clinical development plan (CDP) and minimize its risks by tailoring the trial to a specific population as algorithms can predict and gauge the trial’s effectiveness in the subpopulation. It can also angle the trial towards another indication if algorithms show that the indication is more effective.

AT IQVIA Biotech, a series of processes are adopted to gather and standardize the internal data assets that can be leveraged for efficient trial design. Other resources offered include the modelling of multiomic data and patient responses, and knowledge graphs that can identify patterns for drug repurposing.

Indeed, increasing standardization, aggregation and collaboration will unfold the potential of AI and ML in the Research and Development space moving forward.

Staying ahead in the world of trial design and planning

Incorporating robust design into this continuum is one of the ways that biotech companies can stay ahead of the game. Thinking about commercial and regulatory success is also important when developing the CDP.

For example, at IQVIA Biotech, we have helped a pharmaceutical company achieve regulatory approval and reimbursement with its oncology trial by using a standard of care arm that gathered the necessary commercial evidence needed, even if it is randomized.

Here are some recommendations to help companies achieve trial efficiency:

Analyze the commercial situation and apply it to the CDP.
Leverage real world commercial data to ensure the development strategy is aligned with real world medical practices.
Explore the use of simulation and statistical optimization for trial designs of medium and high complexity.
Design individual trials using the same set of assumptions and analytics listed in the CDP.
Keep budgets, timelines, and consistency of the evidence in mind during the trial. Ensure that progress in these areas is fed back into the CDP.
Partner with reliable Contact Research Organizations to support the trial. For example, IQVIA’s IMS ecosystem has the clinical development capabilities and market knowledge to advise markets on where a molecule would succeed in in terms of uptake and market size.

Summary

The benefits of adopting a master protocol can be seen with its increased uptake in Asia Pacific. Selecting the right protocol and trial design based on the CDP is the first step to ensuring data integrity and safety for patients who need it most.

In addition, biotech companies that leverage on AI, ML, real world and multiomic data can enhance their innovative trial design process, optimize their asset, achieve clinical effectiveness and regulatory success and gain market success.

IQVIA Biotech’s Connected Intelligence™ system is one of the tools that companies can use to achieve these successes, as it creates connections across unparalleled data and analytics to discover new insights, drive smarter decision-making and ultimately help companies get treatments to patients faster.

For more information on new approaches and trends in the biotech landscape, do listen to our mini four-episode podcast series, Through the Biotech Lens: Molecule to Market, for Emerging Biopharma where industry stalwarts give an insightful perspective on biomarker selection, innovative trial designs, decentralized trials and the value of digital to advance patient centricity.

IQVIA Biotech employs a flexible and adaptable approach to align with each customer’s needs. The process begins with the initial alignment meeting where we listen to our customer and have an open conversation in order to outline the approach and discuss the most efficient way to perform the study. This helps clarify the scope of the trial, allowing for the development of a sound strategy and to ensure the work is achieved in a timely, efficient manner. Our goal is to help our customers get their life-saving therapeutics to commercialization as efficiently and cost-effectively as possible so that patients can receive the treatments they need.