Pre-Clinical: Laying the Right Foundation

February 6, 2020
Agnes Shanley
Pharmaceutical Technology
Volume 44, Issue 2

Quick approval pathways challenge teams to balance compliance with the need for speed.

Successful drug development depends on work done before clinical trials begin. As innovators outsource more of their discovery and  research, contract research organizations (CROs) are taking over more early development activities. Their involvement typically begins by helping sponsors determine the best target therapies to pursue, after which pre-clinical in-vitro and in-vivo testing evaluate the toxicity and optimal dosage of these therapies. 

One crucial area is pre-clinical testing, which bridges drug discovery and clinical research stages, and encompasses functions such as pharmacokinetics and toxicology testing, animal research, and cell line and assay optimization. Globally, demand for these services is expected to grow by 6.6% per year to reach $5.2 billion in 2024, according to a 2019 market research report by Market Research Future (1). 

Geographically, the Asia Pacific market is registering the fastest growth, at 9.4% per year, while demand in North and South America, which account for over 40% of the market, is expected to grow by nearly 7.5%. Pharmacokinetic studies are the fastest growing pre-clinical services sector, increasing by nearly 9% per year, according to the data analysts, while toxicological studies represent the leading market segment and are expected to reach nearly $2.5 billion by 2024.

Restructuring has reshaped the pre-clinical contract research organization (CRO) market over the past few years, as specialists have merged or been acquired. Most large diversified CROs have expertise, not only in pre-clinical services but also in clinical and discovery. The past three years have seen IMS and Quintiles join to form IQVIA; LabCorp merge with Covance and Chiltern; Icon and MAPI combine; and Eurofins Scientific acquire the pre-clinical specialists Alphora Research, Selcia, and Amatsigroup. 

Outsourcing is the only way for virtual companies and charities without internal resources (i.e., hospitals and institutes developing therapies for rare diseases) to develop their own pipelines, with projects set up so that sponsors can tap into and manage multidisciplinary teams. But even for larger companies with internal R&D assets, outsourcing has become a way to improve capital efficiency and elasticity, and reduce overall cycle times, says Vicky Steadman, general manager of Eurofins Integrated Discovery. Her division focuses on identifying the best drug candidates for pre-clinical studies, which are then carried out by other divisions of Eurofins. 

Companies have already reduced cycle times, but abbreviated regulatory approval pathways have made it even more challenging to balance the need for speed with the mandate to meet FDA’s current good laboratory practices (CGLPs) requirements. Illustrating what can go wrong at the pre-clinical research phase, in October 2019, FDA issued a warning letter to Novartis’ subsidiary AveXis, citing problems with data from early animal studies for its new therapy, Zolgensma, a treatment for the rare disease spinal muscular atrophy (2). The company had only alerted regulators to problems with the data after the drug was approved. In addition, regulators found other CGLP issues at the lab, including unexplained discrepancies in potency assays, incomplete records, and failure to follow testing protocols or quality assurance procedures. 

Paralleling CGMP problems found in recent FDA warning letters for manufacturing, recent CGLP citations for pre-clinical testing often emphasize lack of root cause analysis and corrective action, and failure to follow testing protocols and standard operating procedures (3). 

 

 

Compliance with CGLPs

One of the most important aspects of any pre-clinical collaboration between a sponsor and CRO is ensuring that work meets CGLPs and other regulatory requirements. That is not necessarily difficult, but can be more challenging than it sounds, says Nancy Catricks, executive director of regulatory compliance at the CRO, Charles River Laboratories. The fundamental requirement is establishing appropriate quality systems at the testing facility, she says. 

Nonclinical safety studies are legally required to be conducted according to CGLP regulations if they support or are intended to support applications for research or marketing permits for products regulated by FDA, she says. “CGLPs were enacted to assure the quality and integrity of study data and reduce the chances of unreliability and fraud. Following these regulations appropriately assures that studies are reliable and allows FDA to make sound decisions for patient safety.” 

Ensuring data integrity remains a key challenge, as shown by the AveXis warning letter, and many CROs have established formal methods and teams to make sure that it gets the attention it requires. Charles River, for example, has set up an internal data integrity governance committee made up of key business and regulatory executive leaders, to set goals and assess performance. The company articulates its approach and expectations for data integrity in a global quality policy and has two different plans in place for the business: a global data integrity compliance plan for all its divisions and a CGLP-specific compliance plan. “Extensive CGLP training, with a focus on data integrity throughout, is included in the training program for personnel engaged in pre-clinical work,” Catricks says. All equipment and instruments that are used in CGLP studies are subject to stringent validation and qualification requirements, she says, based on standards that ensure data integrity.

“The assurance of data integrity is not a new expectation or concept, but over the past few years there has been an increased focus on data integrity within the industry. I think there are times when staff at laboratories that are conducting CGLP work may not have a full understanding of the CGLPs or the quality systems that must be in place to ensure the CGLP regulatory requirements have been met. Unfortunately, this will result in studies that cannot be reproduced and will lead to instances in which FDA rejects studies because the agency cannot confirm data integrity,” Catricks says.  

She suggests process mapping as a useful tool for laboratory managers who want to improve or enhance their pre-clinical research programs. This approach requires staff to take a critical look at all the steps involved in a particular process to determine whether there are any that are unnecessary or do not add value, and then remove those steps. It also calls for a close examination of areas where there may be gaps in data integrity.

Laboratories interested in establishing a CGLP program should engage with partners that understand CGLPs, including the preambles, and have expertise working in an established CGLP environment. “Simply reading the CGLPs is not sufficient,” Catricks says. 

New tools streamline efforts 

Both sponsors and CROs are using or developing new tools to improve pre-clinical testing efficiency. A number are working with machine learning. One such tool is the pre-clinical data integration and capture tool, PreDICT, developed by AstraZeneca and Tessella to access, share, and analyze different types of pre-clinical data. The software can predict optimal doses and scheduling. So far, AstraZeneca reports using it for more than 150 projects, and notes that it has saved 30% of the time usually required for pharmacokinetic/pharmacodynamic models. In addition, the company claims that use of the software has saved 1.5 to 2 days of study time for drug, metabolism, and pharmacokinetics as well as bioscience studies (4).

Also leveraging machine learning is Riffyn, a company that started up six years ago, which offers a cloud-based platform, SDE, short for Scientific Development Environment, for pre-clinical and other development work. The software incorporates principles from Six Sigma’s define, measure, analyze, improve, and control (DMAIC), quality by design, and measurement systems analysis, says CEO Tim Gardner. Riffyn’s initial experience was in industrial biotechnology, where SDE was used by the enzyme manufacturer Novozymes to increase capacity by an order of magnitude and cut time to mmarket by a factor of two, Gardner says. The company is now working with a number of pharmaceutical and biopharmaceutical companies on pre-clinical and other development programs, including bioassays, formulations development, and bioprocess development.  

As Gardner explains, SDE is really a digitized Process Lifecycle Management environment. “It’s built around mapping production and analytical process designs and specifications and then accelerating the improvement cycles of those processes until they are ready for transfer to manufacturing.” In bioassay development for one pharmaceutical client, Gardner explains, the tool allowed users to cut 2400 hours per year out of the lab time required for assays, halving workload for a group of four.

Clearly, machine learning and artificial intelligence, which are already playing a more dominant role in drug discovery, promise to be used in more pre-clinical work, and beyond, in the future. Not only sponsors, but a growing number of CROs and contract development and manufacturing organizations are actively exploring the technology’s potential. 

References

1. Market Research Futures, The Global Pre-Clinical CRO Market, 2019. 
2. J. Wechsler, “Data Integrity Scandal Prompts FDA Probe,” Pharmaceutical Executive, 39 (10) (2019). 
3.  FDA, “Warning Letter to American Pre-Clinical Services,” fda.gov, February 12, 2019.
4. Tessella Ltd., Rethinking Pre-Clinical Data Collection, tessella.com, 2019.

Article Details

Pharmaceutical Technology

Vol. 44, No. 2

February 2020 

Pages: 54-55

Citation

When citing this article, please cite it as A. Shanley, "Pre-Clinical: Laying the Right Foundation," Pharmaceutical Technology 44(2) 2020.

 

 

 

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