What is your background in preclinical research?
I have a PhD in immunology, and I have spent most of the last 20 years in an academic research setting.
I spent 10 years doing discovery immunology in animal models and in humans and another 5 years in a clinical research space supporting immune monitoring for AAV gene therapy. During this time, I also served as scientific director for a newly-formed clinical manufacturing facility for cell-based therapies, making Car-T, NK cells, NK cells and various tissue engineered vascular grafts for patients. I joined AmplifyBio shortly after launch to add analytics capabilities to complement advanced therapy preclinical CRO work.
What does “analytics” encompass in AmplifyBio’s preclinical work?
Currently, we’re setting up a wide variety of molecular and immunological assays. In the cell and gene therapy space, and in most advanced therapeutics, putting together a study requires a lot of customization. It’s important to structure our strategy for understanding the systems that we work in. We are prepared to design studies that are specific to the gene sequence, the cell type, or the pathway that is being targeted.
Why invest so significantly in building an analytics lab in AmplifyBio’s first year as a spin-out from Battelle?
From inception, AmplifyBio’s goal has been to broaden our capabilities and become true development partners to clients pursuing cell and gene therapies and other advanced therapies.
To do that, in vitro immunological and molecular assessments to complement in vivo work are critical to understanding safety and efficacy. The cell and gene therapy space is so varied that it requires significant effort to be able to cover all the tests that you’d anticipate somebody would ask for.
What are the practical impacts of this characterization being done at the preclinical phase?
In terms of practical benefits, some of the technologies we’re using are made to minimize the number of animals used in a study while maximizing the amount of biological data that can be gathered.
First, a comprehensive data set will facilitate efficient study design, allowing you to make your therapies in a way that is safer but also provides statistical power for making conclusions while minimizing repeat studies.
Second, once you get to phase one clinical trial, you’ll have some guidance and expectation on how to design your study. For example, you may know exactly which time points you need to do immune monitoring, or you might have identified a pathway that you know your therapeutic might modulate, in addition to existing pathways of your disease target. Knowing key biomarkers in advance of a clinical trial is extremely useful when samples available for testing become limiting.
What are the most requested assays you are adding to studies?
The most common molecular assays would be basic biodistribution work and immune profiling.
How does including biodistribution in a preclinical study help make necessary adjustments?
Biodistribution is especially useful to determine where your DNA might be going and for distinguishing that from where your transgene may be expressed.
In the case of a gene therapy vector, it is important to get both the vector DNA and vector transgene data for any given therapeutic.
However, if you want to be able to modulate gene expression, for instance, changing a promoter or a vector capsid, it’s easier earlier on in a client’s preclinical work.
Therefore, potency assays and in vivo distribution studies are one of the most important testing aspects you want to consider when optimizing your therapeutic.
In vivo imaging can complement biodistribution work, allowing you to visually see what might be happening within the biological system of a living organism. This can result in fast data without having to go through all the molecular biology, and you can also get a kinetic analysis so you can see what that looks like over time.
For cancer models, you can track tumor growth along with the in vivo distribution of cancer-killing T cells. All of this is done less invasively; animals can be tracked and monitored over time without having to euthanize.
What is the importance of immunoprofiling assays at the preclinical stage?
Immunoprofiling, whether by gene expression or high parameter flow cytometry, is helpful for understanding pathways that might be modulated by your therapy.
For example, if you are really interested in how stable your transgene is, you could want to look at pathways involved in immune suppression or peripheral tolerance/immunity, either modulated by an associated drug regimen or the vector itself.
You could get a snapshot of the effect of your therapeutic at a certain point in time. Once you identify a pathway, it might be something that you can modulate as part of your therapy, or it could serve as a biomarker for safety.
What technologies or platforms are you using to look at gene expression at AmplifyBio?
We will be offering three primary platforms that will facilitate preclinical testing. First, we have a state-of-the-art, high-throughput digital PCR laboratory to support GLP biodistribution work. Digital PCR is both more accurate and more sensitive than traditional quantitative PCR methods, and we can assist our clients with bridging the two technologies so that they can effectively transition.
Second, we will offer a version of gene expression profiling, called direct read profiling, that is faster and more affordable than traditional sequencing approaches. In an academic setting, much of the effort is spent sifting through and analyzing sequencing data. Although this offers plenty of insight into your biological system, something so time-consuming doesn’t make sense when your goal is to get your product to market as soon as possible.
Third, we will offer advanced high parameter immunophenotyping by flow cytometry using a new technology called spectral flow cytometry. This technology is a discovery platform, and spec allows you to identify new populations of effector cells or pathways regulating these cells in vivo.
What are important technology and methodologies for looking at vector integration?
Vector integration is an important safety concern for new therapeutics moving to clinical settings.
Since it’s important to avoid random vector integration, logically, it’s something that should be analyzed in the preclinical phase. That’s why we’re onboarding long-read next-gen sequencing, which can sequence an entire strand of DNA and identify a chromosome location – a cost-effective and less complicated approach to this type of analysis.
Why did AmplifyBio add immunological testing in parallel with molecular capabilities?
Sometimes during the clinical phase, the immune system comes up, and the response observed wasn’t anticipated from preclinical data. I strongly believe that by collecting more information about identified pathways in animal models at an earlier stage, we can plan for unanticipated events once we get to the clinic.
Among the immunological assays, we added to preclinical studies, some of the most notable come from our onboarding of spectral flow cytometry technology, allowing for very large immunological flow panels at low cost. We can do extensive phenotyping of cells, including not just identifying the lineages but also looking at their development and activation. By using an unbiased 3-dimensional view of phenotypic relationships, we can also discover new populations of interest or regulatory pathways that might play a role in the system.
We also offer gene expression panels focused on inflammation, adaptive immunity, or humoral immunity. That will help identify key pathways involved in an immune response, informing how effective a cell therapy or vaccine might be against a like target.
What is AmplifyBio doing to address the challenge of processing and communicating data efficiently enough to be actionable?
First, we’re onboarding an information management system that streamlines our workflow, allowing us to become essentially paper-free, which gives our study sponsors direct access to their data in near-real time. Like how a clinical lab processes data, our instruments will feed data as it is generated, letting you dial in and look for test results.
Additionally, as multiple technologies are becoming intertwined, we are investing in computing power. That includes servers and lab computers with next-generation processors and ample storage for data analysis, which allows complex analysis of large datasets. It also includes the use of biostatisticians that are familiar with the technologies.
In order to scale our footprint and harness our data, we’ll be leveraging cloud-based computer storage in a compliant way. By having the LIMS, the information management system, and the combination of multiple types of computing options, we will have the ability to get through a large data set in a very short amount of time.
What types of expertise are you adding to the analytics department?
So far, we have added sixteen people to the department, including five PhD scientists. Our lab managers and technicians cover a wide range of expertise which includes cell manufacturing and previous cGMP experience, T-cell immunology, cancer biology, virology, infectious disease, vaccine development, molecular biology, and clinical laboratory testing.
Are there any other technology platforms you are particularly excited about?
I’m also excited about the potential of spatial gene expression platforms, which allow us to look in the tissues. Whether it’s a tumor environment or a target organ, we can look and identify the cell type that the transgene is being expressed in and the cells in the surrounding local microenvironment. By studying the gene expression profile of target cells within a microenvironment, we can understand cell-mediated tolerance mechanisms.
To learn more about the analytics capabilities at AmplifyBio, click here.
