With constantly evolving industry regulations, the increasing pressures to reduce the costs of drug development, and raising demand for new therapies, trends in clinical trial outsourcing strategies emerge.
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There has been an increase in sponsors outsourcing to vendors from 43% to 45% from 2016-2017. This trend has continued and was reported to have increased to over 50% in 2018 according to the Beroe analysis. A further 2018 study by the Avoca Group, comprising 128 recipients (evenly distributed across small to large pharma/biotech), reported that 65% of R&D activities were now outsourced. This trend is predicted to remain stable until 2021.
Have you seen different figures?
Data sources can vary and some conflicting figures show slightly lower numbers in favour of the stable outsourcing percentages seen in Figure 1 from the Avoca Group. We should take into account the year on year growth of R&D spend so despite a fairly flat percentage, the absolute figure increases.
Despite the varying sources, it is all consistent with continued growth. The reasons for the continued growth of the CRO market can be attributed to:
As outsourcing rises, unsurprisingly so does the demand for contract research organization (CRO)-conducted clinical trials. In 2016, the overall bio/pharmaceutical outsourced development spend was $26 billion and was expected to reach $31 billion in 2019.
While the clinical research organization market size (CRO-conducted clinical development) in 2015 was $25.7 billion and is expected to increase to $36.7 billion by 2020,the Beroe Analysis fills some gaps and states $31.6 billion in 2018, and it is expected to grow at a (Compound annual growth rate (CAGR) of 12 % to reach $45.2 billion by 2022. We’ve summarized these data in Figure 2.
Intense competition in this growing market has led CROs to seek competitive advantages wherever they can - consolidation and merging has been the only answer for some as they look to build a more comprehensive portfolio of service offerings. While consolidation serves an important purpose, it also has several drawbacks: less competition and less choice for sponsors could result in large unwieldy organizations that may offer the scale but perhaps not the flexibility or sponsor-focused service that niche providers can offer. In 2019, we saw a clear divide emerge between generic ‘one-size-fits-all’ solutions and more client-centric service providers.
So now that we’ve looked at the CRO marketing growth and the trends on sponsors outsourcing, what are some of actual the hot topics for clinical trial sponsors and vendors alike.
Let’s break these down and take a look.
Functional service provision (FSP) continues to be a core outsourcing model between sponsors and service providers. This involves a vendor providing whole functional teams that support sponsors for specific services. The Avoca Group study showed in figure 3 that larger sponsors split their FSP outsourcing to full service outsourcing by 48% vs 52%, whereas smaller service providers come in at 36% FSP vs 64% full service. It is expected that smaller providers will get closer to a 50/50 model in the near future. This open up a lot of opportunity for CROs, with more and more providers positioning themselves as FSP experts.
Forming a long-term relationship with a CRO across multiple services is growing in popularity. For CROs, this means a more profitable model and the potential for larger contracts and repeat business. For sponsors, it leads to greater efficiencies as CROs understand business models and clinical data and other services are centralized with a single service provider.
Providers indicate that a larger proportion of their revenue comes from FSP than from full-service arrangements (2018: FSP, 57%; full service, 43%). And, like sponsors, they anticipated stability through 2021 in these relative allocations by a future model (2021: FSP, 53%; full service,47%).
In 2019, the industry saw the Food and Drug Administration (FDA) approve the first drug (Pfizer’s Ibrance) where analysis was largely based on real world data (RWD). The demand for Real World Evidence (RWE) is increasing due to the growth of rare disease studies and rising clinical trial costs, as well as the emergence of technologies to capture data outside of a clinical trial - we should expect more RWD within our study protocols in 2020.
RWD collected through observational studies outside of the traditional clinical setting holds great potential for rare disease trials where it’s more difficult to recruit for smaller patient populations and fund a full-scale randomised clinical trial.
The correct collection of RWD is essential to facilitate its analysis and prove drug efficacy, and this must be factored into a clinical trial at design stage. Clinical Registries, Electronic Health Records (EHR) and post-authorisation reports are just some of the sources for RWD. It is important for CROs and pharma to have a handle on how to use these data and also to be aware of latest technologies for processing such data. Some examples include Clinical Pipe which connects EHR to Electronic Data Caputre (EDC) systems, and Medable where RWD, eSource, and all other EDC systems are centralized in one platform for analysis.
Some of the most promising eSource technology advancements for future research are considered to be:
There are approximately 7,000 distinct rare diseases affecting 350 million people worldwide and more studies than ever are now being conducted. The FDA has more than 700 active Investigational New Drug Applications (INDAs) for gene and cell therapies alone and approved two cell-based gene therapies in 2017. It is anticipated that gene therapy will become a mainstay treatment for many rare diseases.
We expect to see more new drugs and personalised medicines for rare diseases and emerging biotech’s honing in on this market, as well as increasing interest from large pharma.
As these studies are complex in nature, the price of drug development is high. While in most cases patients struggle to finance them, hospitals and insurance agencies usually pick up the bill and pay for the treatments. There is a sense of pride and achievement in the industry when a successful INDA for a rare disease is made as gene altering treatments are often viewed as one-time-miracle-cures, and that is something pharma wants to be a part of.
Artificial intelligence (AI) and machine learning (ML) have been gaining momentum in the pharmaceutical industry. In relation to the statistical programming of clinical data, there are significant opportunities afforded by advanced programming and developing sophisticated automations to bring efficiencies and thus reduce timelines and improve productivity.
One of the more promising potential uses for using AI and ML in clinical trials is in the design phase. ML can be used to read hundreds of thousands of study protocols and the results of trials, and then provide automated advice during protocol development of the study design, with the goal of the first protocol draft being drafted by machine.
There is currently very little use of ‘real’ ML and decision making by AI using supervised, unsupervised or reinforced learning in programming clinical data. But, with advancements in AI there is the possibility of a future which uses AI to evaluate RWD, such as electronic health records, to perform virtual clinical trials, thus decreasing the requirement for real clinical trials. Technological advances like these will require agility from the regulators so that guidance can be developed quickly enough to ensure that the promises of AI can be realised.
One of the key factors within the ICH GCP E6 R2 Addendum was the adoption of a risk-based approach to clinical trials. Risk Based Monitoring (RBM) was already rising in popularity prior to the addendum release, and was further strengthened by release of the new guidelines in 2017. 2019 has seen this approach evolve to encompass other areas not just focus solely on monitoring.
So if it is more than just monitoring what can a Risk Based Approach look like?
The following should be included:
The above should Implement risk controls and take corrective action during study conduct, which should all be included in an auditable log.
Due to this it can be argued that RBM has evolved to Risk-Based Quality Management (RBQM) which covers a broader remit of;
So what does this all mean in 2020?
It opens the door for a holistic risk-based approach focusing on oversight and improving data quality to ensure a successful regulatory submission. A myriad of possibilities exist to improve data quality, which as per the ICH GCP E6 R2 Addendum, sponsors, vendors and supplier should abide by.
Lets just remind of ourselves of this: “Pharma organizations are responsible for the quality of data collected through clinical trial execution even when outsourced to a CRO.”
The ICH GCP E6 (R2) guidelines tell us that CRO oversight is key. 2019 saw sponsors adopting more effective methods for clinical trial oversight in relation to metrics, deliverables and quality, including outsourcing to CROs. This resulted in niche CROs performing data quality oversight, and regular quality checks on monitoring and study data, even when another CRO has performed the monitoring. This is because another CRO may not have had the technology or systems in place to perform the required statistical checks for data quality, or may not have been comfortable disclosing shortfalls in this area to the study sponsor.
Data Integrity is the maintenance of, and the assurance of the accuracy and consistency of, data over the entire life-cycle.
The evolution of RBQM also includes a focus on data quality and this complements the approach to data integrity recommended by the ICH GCP E6 R2 addendum. These data integrity standards can be attained for a range of other statistical analyses, not only clinical data. Centralized statistical monitoring can achieve this via the detection of data anomalies, outliers and potential fraudulent data across these various data sources. 2019 saw an increase in the demand for these data analytics in response to the regulators requiring more evidence on overall quality assurance and improved patient safety.
We expect to see more successful Real Time Oncology Review (RTOR) studies as they can be especially beneficial for drug development in this therapeutic area. RTOR is a process where an early review of data can be made by the regulators prior to full application of the regulatory submission. This marks a significant step forward in clinical research as it can significantly reduce the approval time without compromising safety and effectiveness of treatment.
The RTOR model allows the FDA to review the data much earlier, and approvals could occur in 2-24 weeks compared to 6-10 months, which brings obvious benefits in reducing overall costs of clinical trials and getting novel treatments to patients much faster. This is facilitated in part by the RTOR study design making use of the RWE and outcomes research which we previously highlighted as an important factor in 2020. While many pharma firms are running their own pilot studies in the oncology field, we should expect this approach to be rolled out to other therapeutic areas where it can also bring the same advantages to sponsors.
There will be increasing pressure on drug/device developers to ensure that each INDA/NDA successfully passes at first submission due to factors such as the increasing cost of clinical development. Precision medicines are now more expensive to produce than traditional medicines which leads to a squeeze in profit margin and increased pressure to produce a successful first-time submission and avoid any costs associated with resubmission. Traditional medicine R&D costs are also increasing and are estimated to reach just under $2 billion in 2017 up from $1.2 billion.
The emergence of RTOR, increases in the use of RWE, observational studies and advancements in technology to capture more real time data, will require trial designs to evolve in concert.
The industry is moving away from the gold standard of RCTs in favour of more bespoke trial designs that can be more appropriate in certain circumstances. For example, RCT designs give no opportunity to change treatment allocation probabilities whereas adaptive clinical trial designs, and especially response adaptive randomisation (RAR) designs, allow treatment allocation probability to vary. If one treatment is seen to perform better than others, this type of trial design can allow patients to be allocated to the better performing treatment halfway through trial. This can only be beneficial for the patient and often for the drug company too.
This approach is often more efficient, informative and ethical than traditional fixed designs, and they often make better use of time and money, improve patient outcomes and may require fewer participants.
RAR is just one example of a novel design that doesn’t follow the RCT gold standard and we should expect to see more of this type of trial in the coming year alongside other novel designs.
The imminent application of Clinical Trial Regulation (EU) No. 536/2014, estimated to happen in 2020, will promote an era of transparency. The regulation applies to all interventional clinical trials (Phase 1 to 4) performed in the European Union (EU)/European Economic Area (EEA), plus additionally specified paediatric trials, and covers documents at the single clinical trial level irrespective of the drug’s marketing approval status. The regulation requires the disclosure of clinical trial documents including a Plain Language Summary (PLS; also known as a Laypersons Summary) for each clinical trial. Disclosure is readily welcomed by study participants who often want to know what has been learned from their participation in trials. Sponsors will have to develop processes and dedicate resources to clinical disclosure activities. Medical Writers will play a key role in this process to ensure correct presentation and standardisation of disclosure documents, which will be available to the public, and ensure that a clear understandable writing style is used for all documents.
At Quanticate we specialise in collecting, analysing and reporting clinical and real world data, across statistical programming, biostatistical consultancy, clinical data management, pharmacovigilance, medical writing and regulatory submission review services. Whatever the data, we’ve got you covered. If you are looking for support on any of the topics highlighted in this blog please Submit a RFI and member of our team will be in touch with you shortly.
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