Analytical Controls in an Evolving Technology and Regulatory Landscape

 
IBC's 18th Annual TIDES is the industry's #1 forum for oligonucleotide and peptide leaders to build successful partnerships and accelerate products from early discovery through late-stage development and commercialization. The TIDES team recently talked to Rachel Orr, Senior Scientist, GlaxoSmithKline R&D, United Kingdom for an exclusive interview that delves into analytical controls in an evolving technology and regulatory landscape, the topic of her presentation at the upcoming Oligonucleotide and Peptide Therapeutics event in Long Beach, CA.


1. What key analytical challenges do oligonucleotide developers need to overcome in order to achieve regulatory approval?

Oligonucleotides are inherently difficult to analyze - they are neither traditional, small nor large molecules, and the techniques and well established methodologies for pharmaceutical analysis are all focused on these distinct classes. In addition, there is very limited regulatory guidance when it comes to oligonucleotides, so there are no set rules to follow. There are often discussions as to whether oligonucleotide analysis should follow small molecule rules and regulations or align with biopharmaceuticals; opinions are divided.

With limited experience across the industry in marketing applications it is difficult to assess what is needed in order to gain regulatory approval and this is one of the biggest challenges in CMC oligonucleotide development. There is no recent precedence of global oligonucleotide marketing applications and as such it is difficult to ascertain what may and may not be acceptable. Close engagement with the regulators is something which helps to form strategies and controls and hopefully this will increase the likelihood of success of regulatory approvals going forwards.


2. How have advancements in technology improved the analytical process? Can you provide examples?

Since the last successful oligonucleotide marketing application there have been considerable enhancements in technologies. UHPLC is now common throughout the industry and techniques such as high resolution NMR and mass spectrometry are much more affordable and quick. These advances in technology mean that the resolution and robustness of methodologies can be much improved, however has a downside that the regulators may well expect us to present them with these improvements by first intent.

Increased understanding of non "typical" molecules throughout the industry has enabled wider thinking and collaboration between different pharmaceutical companies, with more people working together on the problem progress will inevitably come quicker. As more people engage with the concept of oligos and as technology continues to evolve, I anticipate a large shift in the way we look to control oligonucleotides analytically in coming years.


3. What are the most common mistakes that oligonucleotide drug developers encounter during CMC submissions?

Again, due to there being so few oligonucleotides which have gone through the full CMC process I think it is difficult to make too many sweeping statements, however the key issues that I have come across all stem from attempting to fit oligonucleotides into a box. Whether it is the small molecule group or the biopharmaceutical groups who take on the challenge of oligonucleotides, it is generally only a few "experts" within that team who work on the molecules. It is impossible to fit existing small or large molecule platforms onto oligonucleotides and a lot of time, resources and money can be wasted trying to do so! Due to the small pool of people working on the oligo projects it can also be challenging when it comes to elements such as wider reviews of submissions as the reviewers are not always as well informed about the challenges associated with oligonucleotide analysis. Education of these reviewers and key stakeholders is an activity that cannot be underestimated in time or importance! This emphasizes the benefits of cross-pharmaceutical company collaborations.


Want to hear more from industry experts like Rachel? See our exclusive TIDES speaker Q&A series here.

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Implementing Equivalence Testing for the Evaluation of Parallelism: Insights from Dr. Todd Coffey

In today's blog post, Biological Assays presenter Dr. Todd Coffey, CMC Statistician, Seattle Genetics, share with us a  little about his work in evaluate parallelism for bioassays.  Here's what he had to share.

One of the criticisms of the equivalence approach for assessing similarity is that development teams will inadvertently utilize compromised samples and implement a too-wide “zone of indifference”. How do you protect against this problem?
Compiling a set of historical data that includes the natural variability of parallel curves is not a trivial exercise. I offer three suggestions to protect inadvertently against including compromised samples: 1) Ensure the dataset is large enough to include all sources of assay variation. With an adequately large dataset, patterns can often be identified that may elucidate which samples are compromised and why they should not be included with the other parallel samples. 2) Carefully assess the data for unusual trends and patterns, both visually and with statistical analysis. 3) Compare the parallelism metric for degraded samples that are expected to be non-parallel to parallel samples that are suspected of being compromised.

The USP states that one can use the absolute difference of slopes or a ratio of slopes when using the equivalency approach for similarity. Do you have a preference and why?
Using ratios has the advantage of being generalizable across assays. However, calculating confidence intervals on the ratios is not always straight-forward because the ratio of two normally distributed variables is not normally distributed. Thus special care has to be used to correctly calculate confidence intervals on ratios. While not as generalizable across assays, calculating differences between standard and test is more straight-forward statistically and is also interpretable. For these reasons, I prefer to set equivalence limits using differences

How many reference vs. reference runs do you recommend using to establish a “zone of indifference”?
There are at least three issues to consider when discussing sample size. First, to be representative, the number of runs needs to include all sources of variation. Second, the sources of variation have a great impact on the relative value of measurements and the sample size is dependent on getting the right data. For example, if most of the assay variation comes from factors that vary between runs, then many measurements in the same run are of much less value than measurements from different assays. In this case, the sample size is dependent more on the number of times the assay is run after varying the factors that cause the variation. Finally, to provide accurate estimates of tolerance intervals, the sample size of independent measurements generally needs to be several dozen. When that sample size is not attainable, I recommend setting initial limits, monitoring the assay, and then modifying limits as new data emerge.

Many companies start with a difference approach to similarity during early product development when they have a small number of lots and the assay is still being developed. At what stage of development is it reasonable to implement an equivalency approach for similarity?
I recommend using the equivalence approach when there is an adequate set of representative historical data that contains all sources of variation. Sometimes this dataset is available during qualification or before the IND is submitted. If it is not available then, the next potential milestone may be when process characterization activities begin.

Dr. Coffey will be presenting Tips and Tricks for Implementing Equivalence Testing for the Evaluation of Parallelism this May 14-16, 2013 in Seattle, Washington at the Development, Validation and Maintenance of Biological Assays event.  For more information on his session and the rest of the program, download the agenda.  If you'd like to join him, as a reader of this blog when you register to join us and mention code IBA13JP and save 20% off the standard rate.  Have any questions?  Feel free to email Jennifer Pereira.

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Live from Central Labs: Day 3

Central Labs Partnering event closed today which a motivational keynote from Lou Ferrigno. Pharmaceutical executives listened as Mr. Ferrigno explain how becoming fearless and taking strategic risk in this economy will lead to true success and breed innovation. In the afternoon, Wendy R. Sanhai, PhD, Senior Scientific Advisor, Office of the Commissioner, FDA; Samir Khleif, Head, Cancer Vaccine Section Investigator, NIH; William Wheeler, MD, FAAC, Global Medical Director, Centralized Cardiac Services, MDS PHARMA SERVICE; and Patrice Hugo, Vice-President of Scientific Affairs, MDS PHARMA SERVICES provided innovated strategies for working together to develop biomarkers for safety monitoring and surrogate endpoints.

IIR would like to thank all of those who attended and invite you to comment here on the event. We are looking for ideas on where to hold next year’s meeting and welcome your feedback here.

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