“To consult the Statistician after an experiment is finished is often merely to ask him to conduct a post mortem examination. He can perhaps say what the experiment died of.”
– Ronald Fisher
The role of a Statistician is instrumental in bringing new medicines to patients – from the planning of first exploratory trials through to informing post-approval publications’ strategy and analysing real-world data to inform reimbursement.
The proper statistical input at the right time can help to accelerate development and bring new medicines to patients, faster. Other quantitative professionals such as statistical Programmers and data scientists also play vital parts in generating evidence from the available data.
As well as needing to be technically adept, Statisticians, in particular, need to be strong leaders and influencers with the ability to communicate complex analytical issues to non-quantitative colleagues.
In the board room, it’s increasingly common to find Statisticians working alongside Chief Medical Officers and clinical stakeholders to provide strategic direction.
Below, we highlight a few ways in which Statisticians and quantitative professionals are quietly changing drug development for the better and delivering new medicines to patients more quickly.
Novel trial designs
Innovative trial designs are a promising strategic tool to help increase efficiency, improve data quality and speed development.
Statisticians work closely with clinical experts to identify whether innovative designs are suitable, inputting into the protocol, running simulations and communicating any trade-offs to stakeholders.
Without access to statistical expertise, sponsors may miss opportunities to streamline their clinical trial programs through innovative approaches. While not every trial would benefit from using a novel approach, considering the full gamut of options is essential at initial planning stages.
New methods that are becoming more utilised include:
Adaptive trials make prospectively planned changes to an ongoing based on accumulating data while ensuring statistical validity. Adaptive designs can accelerate trials by combining phases, making better use of scarce patient resources, and obtaining more, better quality data about the drug. Adaptive trials range from more well-established strategies such as sample size re-estimation, to biomarker adaptive approaches.
Master protocols encompassing basket trials, umbrella trials, and platform trials are innovative designs that aim to answer multiple questions through sub-studies under a single protocol.
Basket trials, for example, have been used in oncology development in response to the development of therapies that target genomic alterations in tumours to investigate response across indications or populations. Platform trials are a type of master protocol that randomise patients with a single condition to different therapies. One prominent recent example is the RECOVERY trial for COVID-19 that assessed the efficacy of various treatments against a single mortality endpoint.
Trials incorporating real-world data
Real-world data is becoming increasingly important in clinical development and reimbursement, and Statisticians and data scientists have a crucial role in helping to turn that data into evidence. One application of real-world data that recently received particular attention is the synthetic control arm, which uses data from other clinical trials and the real world instead of a traditional control.
In the context of the disruption to clinical trials caused by COVID-19, synthetic controls were hailed as a way to augment clinical data or even rescue trials that may otherwise have faltered. Statisticians’ input is crucial to ensuring these proposals are robust.
Supporting data collection and improving efficiency through standardisation
Statisticians liaise with data managers closely to inform the creation of the CRF or eCRF and ensure that the right data points are collected to ensure the proper analysis further along in the workflow. Statisticians are also well placed to spot if there are any data anomalies or potential for balance.
Data standardisation is critical to ensure easy integration and analysis of data from across sources and trials. Standardisation increases the efficiency of data analysis, minimises rework and helps regulatory review. In the future, even greater opportunities exist to improve efficiency further through end-to-end metadata-driven automated analysis of clinical trials – allowing sponsors to fully realise the benefits of our technological and data capture advances.
In the context of new data sources, innovative trial designs, advanced analytical approaches and automation, the role of data scientists, statisticians and programmers will be more instrumental than ever. With both the stakes and opportunities high, sponsors must ensure that they have the right strategic and operational analytical resources on board to support them throughout the drug development journey.
Veramed can support you on the Drug Development journey, whether you require a long-term Functional Service Provider (FSP) or short-term biostatistics consultancy. Get in touch with us today.