"The art of guessing in preclinical research" - a beginner's guide.

The development of biotherapeutics, vaccines, cell & gene therapies is a complex process requiring careful consideration of many factors, including #immunogenicity and #immunotoxicity. But as Confucius once said:

Learning without thought is labor lost; thought without learning is perilous.

Biopharma companies have long understood this, and are now shaping their pipelines so to learn from their candidates (improving selection process efficiency) and increase their predictivity (for better efficacy and safety in the clinic). This sounds like the perfect recipe to reduce guesswork in preclinical research.

But if that is so easy, why are we seeing clinical trial failure rates touching almost 90% across the board? (Wong et al., 2009) This only begs the question: what is wrong in preclinical research? Or better yet: What can we improve?

I was talking this week with an immunogenicity expert at one major Pharma company, and one of the questions from the FDA was on the table:

How do you make sure that the donors you use for your assays didn't have any recent infection?

That was the moment in which I realized that not only the Biopharma industry had a problem, but the Life Science industry as well.

That little predictivity problem...

The issue starts with answering the questions: given the common assays on the market, where do we start, which parameters do we chose, how do we set the controls, which protocols do we use, what is good and what is bad?

Well, that's the problem..

There is no clear answer to this, and authorities struggle with the topic as well.

The selection of the most appropriate assay depends on the product, target, and sample type. CROs and specialized companies have however developed mostly proprietary protocols, and standardization is a massive issue.

The accuracy of these assays can be affected by several factors, including the quality of the starting materials, the specificity of the assay, and the controls used. Especially for the cell-based assays, proper sampling, donor control before donation and proper testing of the cells for their activation potential before the assay allow to set the right baseline and avoid false positives/negatives.

Bonus point, it allows to answer sneaky questions from the authorities.

While assay accuracy is defintely an important issue, an equally important issue is the representativeness of the assay, specifically how the HLA coverage reflects the distribution of the general population.

To improve the predictivity of immunological assays, it is therefore important to use a diverse panel of donor cells to cover a broad range of HLA types, eventually including samples from healthy and diseased individuals. Especially for diseases in which the immune system is affected, testing for immunogenicity and immunotoxicity on healthy donors can be misgiving... to say the least.

One fits all?

Clearly, no. But some steps can be taken to improve predictivity:

1. Choose the right assay: Select the most appropriate assay based on the product, target, and sample type. For example, a cell-based assay may be more suitable for complex biologics than ELISA.
2. Use relevant positive controls: Positive controls should be selected based on the product and target. For example, a positive control for a monoclonal antibody may not be appropriate for a vaccine.
3. Optimize the biological materials: Assay conditions should be optimized to minimize false positives/negatives. For example, using activation-certified cells can prevent testing candidates with exhausted or pre-activated cells.
4. Increase donor control: Make sure you receive as many information as possible from your donors in order to objectively evaluate your results. Data on recent infections, diseases or vaccinations can be useful to interpret assay results.
5. Include relevant HLA types: Ensure good coverage of HLA by including a diverse panel of donor cells to represent the general population. Include healthy as well as diseased donors if needed.
6. Consider the impact of pre-existing immunity: Pre-existing immunity to the product or its components may affect the immunogenicity and immunotoxicity assays. This should be taken into account when selecting samples and designing the assay. Testing the product with plasma from the donor can help identifying pre-existing antibodies.

Conclusion:

The development of biotherapeutics, vaccines, cell & gene therapies has been long suffering from a poor predictivity issue. My suggestion to developers is, ironically, to focus on the basis: choose appropriate assays, use relevant controls, optimize biological materials, increase donor control, and consider pre-existing immunity. My hope is that an increased control of preclinical safety labs on their assays will lead to the creation of standards and sharing of protocols that may positively affect and accelerate the development of new therapies across the board.

What are some other challenges you have faced when developing immunological assays for biotherapeutics, vaccines, cell & gene therapies? How have you addressed these challenges?

I would be happy to hear your thoughts and experiences in the comments section!

Also, you can contact me at [email protected] or visit our dedicated page if you want to learn how we can help you with your unique assays!

#immunoassay #cellandgenetherapy #researchanddevelopment #vaccines #biotherapeutics #celltherapy #preclinical #preclinicalresearch #safety #immunesystem

About Biomex:

Biomex is a leading provider of biological raw materials and services, with over 25 years’ experience in serving the Life science and Diagnostic industry. We produce over 90% of our materials internally through our two plasma centers in Germany and our international network. Based in Germany, our state-of-the-art laboratories and extensive sample inventory, including healthy and diseased samples, make us a reliable partner for the industry worldwide. We offer a wide range of services and access to our inventory via our online SampleShop platform. Visit us at www.biomex.de.

Definitions:

Immunogenicity refers to the ability of a substance to stimulate an immune response: this can be wanted, as in the case of vaccines or immunomodulating drugs; or can be unwanted, in case the immune reaction is directed against a therapeutic agent (usually cell therapies or biotherapeutics), possibly leading to the formation of antibodies that can neutralize or even eliminate the therapeutic agent (anti-drug-antibodies, ADA). ADAs can clog blood vessels or become opsonization targets leading to diffuse inflammation, leading to potential organ damage and decreased drug efficiency.

Immunotoxicity refers to the potential of a substance to cause damage to the immune system, which can lead to adverse effects. An uncontrolled immune response can lead to a cytokine storm, leading to hyperactivation of the immune system and diffuse organ damage and even death.

HLA (Human Leukocyte Antigen) is a group of proteins that are involved in the presentation of antigens to T cells.

References:

Chi Heem Wong, Kien Wei Siah, Andrew W Lo. "Estimation of clinical trial success rates and related parameters."?Biostatistics?20(2): April 2019, Pages 273-286. Published online: 31 January 2018. DOI: 10.1093/biostatistics/kxx069