WHITE PAPER

Cellular and In Vivo Models for Toxicity Evaluation

Introduction

A drug candidate could fail at any step in the drug development process. From an investment standpoint, it is better that a candidate’s failure be identified earlier rather than later. Therefore, it is critical that the studies at each point be sensitive, accurate, predictive, and translatable to the next step. This whitepaper explores how recent advances in preclinical study models show promise for more translatable clinical trial success.

Traditional drug discovery, development, and validation is a multi-stage, detailed process conducted over the course of many years. The process includes well-defined steps [1]:

  • Target identification and validation: Target identification and in vitro evaluation of drug candidates for target affinity and specificity.
  • Preclinical research: In vitro cellular studies and in vivo animal studies on drug candidate safety and efficacy, including dosing and toxicity levels.
  • Clinical research: Human trials conducted in four phases to assess safety, dosage, efficacy, side effects, and adverse reactions.
  • Regulatory review: Application for approval is submitted to the relevant regulatory agency and includes all study data, from early discovery through clinical trials, and recommended dosage and use.
  • Post-approval monitoring: Drug candidates approved for human use are monitored by regulatory agencies for further evolving information about the drug’s safety and efficacy.

Thousands of drug candidates are routinely evaluated during early discovery for a particular disease application, yet only 10% or so are ultimately successful. Many candidates fail during Phase 3 clinical trials, the largest and most expensive of the clinical trials, because of unacceptable toxicity or low efficacy. [2,3] The entire process demands a lot of time, effort, and funding. Getting from discovery to market requires from 10 to 12 years and more than $2.5 billion. [2]

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A drug candidate could fail at any step in the process. From an investment standpoint, it is better that a candidate’s failure be identified earlier rather than later. Thus, it is imperative that the studies at each point be sensitive, accurate, predictive, and translatable to the next step.

Preclinical Research

A drug candidate that passes the rigors of early discovery testing moves into the preclinical research phase. Here it is evaluated for safety and efficacy using in vitro cellular and in vivo animal models. Preclinical studies are required by the U.S. Food and Drug Administration (FDA) and other global regulatory authorities to gain important data on the candidate’s biological effects before it can proceed to clinical trials.

Preclinical studies investigate many aspects of the drug candidate’s activity:

ADMEAbsorption: how bioavailable is the drug candidate and how quickly is it available?
Distribution: how and where is the drug candidate distributed within the body?
Metabolism: how does the body break down the drug candidate and what are the metabolic products and their effects on the body?
Excretion: how are the drug candidate and its metabolites excreted from the body and at what rates?
EfficacyWhat is the effectiveness of the drug candidate at different dosages, and in different species and sexes?
ToxicityHow is the drug candidate and/or its metabolites toxic to the body and at what concentrations, durations, and routes of exposure? Toxicity studies are conducted for different exposures and pathways including acute/subchronic/chronic exposures, cellular/subcellular toxicity, genetic toxicity, reproductive and developmental toxicity, and carcinogenicity.

Preclinical cellular modeling studies are used to identify a drug candidate’s effects at the subcellular, cellular, and microtissue levels. The in vitro cellular modeling data are then used to guide in vivo animal modeling studies.

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It is crucially important that both the in vitro cellular and in vivo animal modeling data be predictive and translatable to humans. Thus, preclinical models must be as physiologically relevant as possible for clinical trial design and outcomes.

In Vitro Cellular Modeling

In vitro cell culture techniques have been used successfully by researchers for more than 100 years. For much of that time, two-dimensional (2D) monolayer cultures were the gold standard in determining the efficacy and safety of drug candidates. In the last few years, however, there has been a push to develop more complex in vitro models that accurately recapitulate the in vivo architecture. Three-dimensional (3D) cell culture and microphysiological systems are part of this cache of complex in vitro models and have become increasingly relevant and important.

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3D cell cultures allow the cells to grow in a natural state, creating a microtissue by establishing connections with other cell types that would be naturally found in vivo, thus giving it a much more natural microarchitecture. This type of culture provides insight into a drug candidate’s impact on cell-cell and cell-matrix interactions in a way that is more physiologically relevant than a 2D monolayer culture. [3,4]

3D Cellular Model Development

Researchers continue to explore ways to make 3D cellular and microphysiological models mimic in vivo human tissue even more closely. One important consideration in the development of physiologically-relevant models is the incorporation of physiological functioning of other cell types into the model.

Endothelial cells form the major component of all blood vessels. Thus, many cell types, both in normal and disease states, interact with endothelial cells. In addition, therapeutic interventions are transported to target tissues via the bloodstream. The endothelial component of tissue and disease function is being studied in regard to the blood brain barrier [5], bone osteogenesis and vascularization [6], vascular smooth muscle cell adhesion and migration [7], tumor angiogenesis [8,9], and others.

A similar consideration with respect to the relevance of 3D models to in vivo architecture is the incorporation of immune components which are normally an integral part of many tissues. Including immune components in 3D cellular models will enhance the relevance of the study data for in vivo animal modeling and clinical trials, such as immuno-oncology therapeutic research. [10]

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The physiological relevance of 3D cellular models can also be improved by mimicking in vivo flow of blood, serum, and growth components as well as secreted factors throughout the culture.

3D Culture Imaging

High-resolution imaging techniques are used to identify and quantify cellular and sub-cellular effects that are indicative of candidate and/or metabolite toxicity. It can be challenging to obtain high-quality imaging from deep within a thick 3D spheroid where there is reduced light penetration, increased light absorption, and light scattering. Specific techniques can be used to help overcome these challenges.

  • The formation of consistently round spheroids that are not attached to the plate or tube supports high-resolution imaging of small targeted areas, thereby reducing the amount of extraneous data generation and processing. It also provides reproducible, uniform data.
  • Confocal imaging yields the highest sensitivity, best signal-to-noise ratios, and highest X, Y, and Z resolution while maintaining high-throughput data acquisition.
  • Water immersion objectives have higher numerical apertures that allow the capture of up to four times more light, and smaller focal depths that reduce the amount of background light and light scattering compared to air objectives. This enables higher resolution that produces crisp cellular details at depth.
  • Use of longer wavelength dyes decreases light scattering and increases light penetration into the 3D sample. This results in improved imaging depth and signal detection.
  • Optical clearing techniques remove the lipid and protein molecules that contribute to light scattering effects, and homogenize refractive indices within spheroids. This increases the imaging penetration depth. Depending on the type of spheroid and what you are trying to investigate, you might need to evaluate different clearing protocols.
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In Vivo Animal Modeling

The next step in preclinical studies is the in vivo evaluation of a drug candidate’s efficacy, safety, and readiness for clinical trials. Thus, the biological relevance of an animal model to human physiology is critical to the predictive value of the model for human studies.

In Vivo Animal Model Development

In vivo animal model design uses ADME and toxicity data from in vitro cellular and microtissue studies to help optimize the model’s biological relevance.

  • Cellular phenotypes and biomarkers of toxicity identified by 3D in vitro studies can be explored further to provide additional or confirmatory data on the relationship between the phenotypes/biomarkers and drug candidate action.
  • The toxicity and efficacy data from 3D in vitro models/studies are used to help refine dosage and treatment time frame parameters for clinical trial design.

Clinical trial design requires a clear understanding of the data needed from upstream animal studies. Some data needs are disease-specific, but much more is driven by regulatory requirements. The data gathered from in vivo animal disease models must also be evaluated for safety and toxicity in the normal counterpart of the same animal models to determine the best in vivo data for use in human trials.

In Vivo Animal Model Imaging

Using real-time imaging of in vivo animal models is an ideal strategy for generating the predictive datasets needed for clinical trial design. [11] Being able to visualize biological events in an anatomical context helps maximize the biological understanding of drug candidates. Such information is useful to confirm and expand upon cellular models, and contributes to translational medicine downstream with the aim of shortening the time to clinical trials.

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Today’s imaging technologies enable the integration of multiple imaging modalities to provide data on different aspects of toxicity, such as changes in anatomy, organ function, and tissue structure and integrity. Imaging even allows observation of a drug candidate’s uptake and distribution, providing an understanding of the candidate’s in vivo pharmacodynamics and pharmacokinetics (ADME).

From a dataset standpoint, in vivo imaging workflows are high throughput and provide robust datasets needed for regulatory evaluation. In addition, obtaining high-resolution images of small targeted areas within a tissue or organ minimizes the generation of extraneous data.

In vivo imaging is non-invasive, making it useful for longitudinal studies. That means more data is obtained from fewer animals, providing cost savings as well as advancing the Reduce, Replace, and Refine (3R) principle of animal research. [12]

Emerging Ideas and Applications

Researchers continue to seek new and innovative ways to make preclinical toxicity and efficacy studies even more biologically relevant for human drug development. Some promising areas of interest include the following:

  • Cellular Biomarkers: Identifying cellular phenotypes and/or biomarkers that better translate to human toxicity and correlate with clinical endpoints; this includes the investigation of non-clinical cellular biomarkers of toxicity for potential extrapolation to clinical endpoints.
  • Natural History Data: Promoting the development of a well-curated data platform that contains information on the natural history of different human sub-populations, with the aim of being able to more specifically evaluate toxicity for different sub-populations.
  • Imaging technology: Integration of artificial intelligence (AI) and machine learning in imaging software. AI shows promise for being able to detect elusive features in tissue areas, while helping to minimize human bias and error.
  • Personalized Medicine: Investigating ways of developing 3D cellular models that can simulate specific patient profiles, advancing the personalized medicine paradigm.
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Summary

These are some of the important considerations, technologies, and innovations that are driving preclinical studies for drug development. Recent advances in preclinical study models show promise for generating ever-more translatable cellular and animal data for clinical trial success. The same preclinical advances are also inspiring clinicians in their search for ways to personalize patient evaluation and treatment.

References

  1. U.S. Food and Drug Administration. The Drug Development Process. Retrieved July 02, 2020, from https://www.fda.gov/patients/learn-about-drug-and-device-approvals/drug-development-process
  2. DiMasi JA, Grabowski HG, Hansen RA. 2016. Innovation in the pharmaceutical industry: new estimates of R&D costs. Journal of Health Economics, 47:20-33
  3. Edmondson, R., Broglie, J. J., Adcock, A. F., & Yang, L. (2014). Three-dimensional cell culture systems and their applications in drug discovery and cell-based biosensors. Assay and Drug Development Technologies, 12(4), 207–218, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4026212/
  4. Yao, T., & Asayama, Y. 2017. Animal-cell culture media: History, characteristics, and current issues. Reproductive Medicine and Biology, 16(2), 99–117, https://onlinelibrary.wiley.com/doi/full/10.1002/rmb2.12024
  5. Campisi, Marco et al. 2018. 3D self-organized microvascular model of the human blood-brain barrier with endothelial cells, pericytes and astrocytes. Biomaterials, 180, 117-129, https://doi.org/10.1016/j.biomaterials.2018.07.014
  6. Chiesa, Irene et al. 2020. Endothelial cells support osteogenesis in an in vitro vascularized bone model developed by 3D bioprinting. Biofabrication, 12(2), February 19, https://doi.org/10.1088/1758-5090/ab6a1d
  7. Xingang Zuo et al. 2020. Spheroids of Endothelial Cells and Vascular Smooth Muscle Cells Promote Cell Migration in Hyaluronic Acid and Fibrinogen Composite Hydrogels. Research, Article ID 8970480, https://doi.org/10.34133/2020/8970480
  8. Amann, A. et al. 2017. Development of a 3D angiogenesis model to study tumour – endothelial cell interactions and the effects of anti-angiogenic drugs. Sci Rep 7, Article No. 2963, https://doi.org/10.1038/s41598-017-03010-6
  9. Sharma A, Shiras A. 2016. Cancer stem cell-vascular endothelial cell interactions in glioblastoma. Biochem Biophys Res Commun. 73(3), 688-692, https://doi.org/10.1016/j.bbrc.2015.12.022
  10. Hirt, Christian et al. 2014. In vitro 3D models of tumor-immune system interaction. Advanced Drug Delivery Reviews, 79–80, 145-154, https://doi.org/10.1016/j.addr.2014.05.003
  11. Oliver, Tamlyn. 2018. In vivo Imaging Roundtable: Building on Breakthroughs. https://www.biocompare.com/Editorial-Articles/353148-In-Vivo-Imaging-Roundtable-Building-on-Breakthroughs/
  12. Törnqvist, E. et al. 2014. Strategic focus on 3R principles reveals major reductions in the use of animals in pharmaceutical toxicity testing. PloS one, 9(7), e101638. https://doi.org/10.1371/journal.pone.0101638

Author Information

Dr. Madhu Lal-Nag (MS, MBS, PhD) is Program Lead for the Research Governance Council, Office of Translational Sciences, at the U.S. Food and Drug Administration. She can be reached at Madhu.Lal-Nag@fda.hhs.gov.

Dr. Anis Khimani (MSc, PhD) is the Head of Strategy and Applications Development, Life Sciences, at PerkinElmer, Inc. Dr. Khimani can be reached at Anis.Khimani@perkinelmer.com.

Note: The information in this white paper reflects Dr. Madhu’s views on this topic and should not be taken as a USFDA endorsement of PerkinElmer.