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Scientists have been investigating cancer for well over 100 years, with the first animal model of cancer being a squamous cell carcinoma induced on the ears of rabbits using coal tar.^1,2 Since that time, many thousands of animal models of cancer have been developed, but they largely fall into one of two baskets: syngeneic models and xenograft models. Both types of models have been used by researchers for over 50 years.^3,4 Understanding the differences between these models, the variations within each type of model, and how to select the most appropriate model is key to designing a successful study – one which will most accurately predict clinical relevance.

Continue reading “Syngeneic vs. Xenograft Cancer Models: Overview, Key Differences, and When To Use Each”

Asthma is a chronic respiratory disease that is estimated to affect 262 million people worldwide and kill approximately 455,000 annually. It is characterized by airway inflammation, bronchoconstriction and airway hyperresponsiveness. These features can significantly impact the quality of life of affected individuals, and although symptom management is feasible, there is no known cure for this condition. The complexity of asthma and the factors contributing to its onset make its treatment and management challenging even for the most experienced healthcare professionals and pharmacologists. One commonly used animal model of asthma is the ovalbumin-induced asthma model. This model involves sensitizing animals to ovalbumin, which is a common allergen, using an adjuvant such as aluminum hydroxide. The sensitization process primes the immune system to recognize ovalbumin as a foreign substance and mount an immune response against it. After sensitization, the animals are challenged with aerosolized albumin, which is delivered directly into the lungs via a nebulizer or inhalation chamber. The challenge with ovalbumin leads to an inflammatory response in the lungs, which includes airway hyperresponsiveness, mucus production, and eosinophil infiltration. In the OVA induced asthma model, this can be measured by assessing changes in lung function, such as airway resistance or lung compliance. Mucus production refers to the increased secretion of mucus in the airways, which can obstruct airflow. In the OVA-induced asthma models, this can be assessed by staining lung tissue with a dye that highlights mucus producing cells. Eosinophilic infiltration is a characteristic feature of inflammatory airway reaction occurring because of asthma. In addition to eosinophils, other immune cells, such as neutrophils, lymphocytes, and macrophages, can also be involved in the inflammatory process of asthma. The levels of these cells in the bronchoalveolar lavage fluid (BALF) can provide insights into the specific inflammatory status and immune responses associated with different asthma phenotypes or exacerbations.

With an estimated total annual cost of $81.9 billion in the United States only (factoring in medical care, absenteeism, and mortality), the burden of asthma on the healthcare system needs to be dealt with swiftly.

Although the exact cause of asthma remains unknown, OVA-induced asthma models have been instrumental in uncovering the underlying mechanisms of the disease.

 

Overview of the OVA-Induced Asthma Model:

Recent studies have continued to use OVA-induced asthma models to investigate the pathophysiology of asthma and potential therapeutic interventions. For instance, a 2021 study by Chelladurai et al. demonstrated that blocking the interaction between OX40L and its receptor OX40 using an antibody reduced airway hyperresponsiveness and inflammation in an OVA-induced asthma model in mice (Chelladurai et al., 2021). Another study by Liu et al. (2020) used an OVA-induced asthma model to investigate the potential therapeutic effects of a novel molecule, FXYD6, which is involved in regulating ion transport in airway epithelial cells. The study found that FXYD6 overexpression attenuated airway inflammation, hyperresponsiveness, and remodeling in the OVA-induced asthma model in mice (Liu et al., 2020).

 

Role of IgE in the Model:

In the OVA-induced asthma model, IgE can play a significant role in allergic reactions by sensitizing mast cells and basophils to ovalbumin (OVA). However, it is important tot note that in order to effectively replicate the model, multiple mucosal OVA challenges are required to drive the IgE-mediated response. Upon re-exposure to OVA, the allergen binds to the IgE antibodies on sensitized mast cells and basophils, leading to the release of various inflammatory mediators that contribute to the development of asthma symptoms. These mediators, such as histamine, leukotrienes, and cytokines, can induce airway hyperresponsiveness, mucus production, and airway inflammation, which are considered important aspects of asthma pathogenesis.

 

Airway Hyperresponsiveness in the OVA-induced Asthma Model:

Several mechanisms have been implicated in the development of AHR in the OVA model. OVA-induced inflammation in the airways can lead to increased airway smooth muscle contraction, which contributes to airway narrowing. This inflammation can be driven by various immune cells such as Th2 cells, eosinophils, mast cells, and basophils. The activation of these immune cells leads to the release of cytokines and chemokines that recruit more immune cells, promote inflammation, and contribute to AHR. In addition, the recruitment of inflammatory cells, such as eosinophils and mast cells, can release various mediators that can further promote airway hyperresponsiveness, such as histamine, leukotrienes, and prostaglandins. These mediators can increase bronchial smooth muscle tone, enhance microvascular permeability, and promote mucus secretion, all of which contribute to AHR.

 

History of the OVA-Induced Asthma Model:

The ovalbumin-induced asthma model was first described in the 1970s and has since become one of the most widely used models for studying asthma (1). The model was initially used to investigate the role of immunoglobulin E (IgE) in the development of asthma. Since then, the model has been used to study various aspects of the disease, including the role of cytokines, chemokines, and other immune system molecules in the pathogenesis of asthma.

 

Comparison of OVA-Induced Asthma vs. Other Asthma Models:

Several animal models have been developed to study asthma, such as the house dust mite model, the cockroach antigen model, and others. While each model has its advantages and limitations, the ovalbumin-induced asthma model is still considered one of the most reliable and widely used models for studying asthma (2). The model is cost-effective and there are genetically engineered transgenic mice available for investigating OVA-specific responses, which is essential for studying the mechanisms of the disease, and for evaluating new biologics. However, it is important to note that no single animal model can fully replicate the complexity and heterogeneity of human asthma.

 

Best Practices When Using the Model:

Using high-quality ovalbumin to minimize batch-to-batch variability, standardizing the animal vendors, and the route and dose of ovalbumin exposure to ensure consistency. Additionally, using a suitable control group to account for any nonspecific effects of ovalbumin and monitoring the animals for signs of distress or illness while ensuring appropriate care are crucial aspects of conducting the study.

 

FAQ:

Q: How does the ovalbumin-induced asthma model compare to human asthma?

A: While animal models cannot fully replicate human disease, the ovalbumin-induced asthma model can provide valuable insights into the underlying mechanisms of asthma. However, caution should be exercised when extrapolating findings from animal models to human disease. For example, there may be differences in the immune response between mice and humans, and ovalbumin may not be a relevant allergen for all patients with asthma.  The OVA model is best used to model patients with a TH2 asthma phenotype.

 

Q: What are the advantages of the ovalbumin-induced asthma model compared to other animal models?

A: The ovalbumin-induced asthma model is one of the most widely used and reliable models for studying asthma. One of the main advantages of this model is the ability to mimics key inflammatory features of asthma, including airway hyperresponsiveness, mucus production, eosinophilic infiltration, and cytokine release. These features closely resemble the characteristics seen in human asthma, making the model relevant for studying underlying mechanisms and evaluating anti-inflammatory interventions.

 

Q: What are the limitations of the ovalbumin-induced asthma model?

A: Like all animal models, the ovalbumin-induced asthma model has its limitations. One limitation is that the immune response in mice may not accurately reflect the immune response in humans. For example, the relative dominance of Th2 immune responses in the ovalbumin model may not fully reflect the immune profiles seen in all types of human asthma, which can involve various immune cell types and cytokines. Additionally, the ovalbumin-induced asthma model is an acute model of asthma that does not fully capture the chronic and progressive nature of the disease. Furthermore, ovalbumin is not a common human allergen, and the model does not account for the contribution of non-allergic triggers to the development of the disease.  The HDM model is more mixed TH1/2/17 phenotype model is also offered by PL,

 

Q: Can ovalbumin-induced asthma models be used to study the effects of therapeutic interventions?

A: Yes, ovalbumin-induced asthma models have been used to study the effects of various therapeutic interventions, including anti-inflammatory agents and bronchodilators. By using these models, researchers can test the efficacy and safety of potential asthma treatments before moving to human clinical trials.

 

Q: What are some best practices for using ovalbumin-induced asthma models?

A: To ensure reliable and reproducible results, it is essential to follow best practices when using ovalbumin-induced asthma models. These practices include using high-quality ovalbumin to minimize batch-to-batch variability, standardizing the animal vendors, and the route and dose of ovalbumin exposure to ensure consistency. Additionally, using a suitable control group to account for any nonspecific effects of ovalbumin and monitoring the animals for signs of distress or illness while ensuring appropriate care are crucial aspects of conducting the study. Furthermore, researchers should consider using multiple models of asthma to validate their findings and to account for the limitations of each model, such as the HDM Asthma Model.

 

Q: Are OVA-induced asthma models only in rodents? What would an analogous asthma model be in non-human primates?

A: Ovalbumin (OVA)-induced asthma models have been primarily used in rodents, such as mice and rats, to study the pathophysiology of asthma and to evaluate potential therapeutic interventions. However, there have been some studies that have also used OVA-induced asthma models in other species, such as guinea pigs and rabbits.

 

Sourcing Your Asthma Study:

Our OVA-induced asthma model faithfully reproduces pulmonary inflammation (eosinophil infiltration), airway hyperresponsiveness, and the elevated IgE levels found in asthma. Coupled with our many years of experience in pharmacology, PharmaLegacy has the expertise and resources to provide comprehensive and reliable preclinical services for respiratory drug development. Choose right when looking for a CRO. Choose PharmaLegacy.

 

References:

1. Alcorn, J. F., Crowe, C. R., Kolls, J. K. (2011). TH17 cells in asthma and COPD. Annual Review of Physiology, 73, 495-516.
2. Carroll, O. R., Pillar, A. L., Brown, A. C., Feng, M., Chen, H., & Donovan, C. (2023). Advances in respiratory physiology in mouse models of experimental asthma. Frontiers in Physiology, 14. https://doi.org/10.3389/fphys.2023.1099719
3. Chelladurai, P., Sehgal, I. S., Dhooria, S., Agarwal, R. (2021). Targeting the OX40-OX40L pathway in allergic asthma: a preclinical study. Immunotherapy, 13(1), 15-27.
4. Das, S., Miller, M., Broide, D. H. (2019). Chromogranin A: a novel mediator of asthma pathogenesis and therapeutic target. Journal of Allergy and Clinical Immunology, 143(4), 1372-1379.
5. Fallon, P. G. (2019). The high and lows of type 2 asthma and mouse models. Journal of Allergy and Clinical Immunology, 105(2). https://doi.org/10.1016/s0091-6749(00)70138-2
6. Fujisawa, T., Joshi, B. H., Puri, R. K. (2019). IL-13 regulates cancer invasion and metastasis through IL-13Rα2 via ERK/AP-1 pathway in mouse model of human ovarian cancer. Molecular Cancer Therapeutics, 18(5), 903-914.
7. Liu, Z., Wang, Q., Wang, J., Yao, X., Huang, J., Yang, Z., … & Lu, X. (2020). Overexpression of FXYD6 attenuates airway inflammation, hyperresponsiveness and remodeling in a murine model of OVA-induced asthma. Molecular Immunology, 117, 1-10.
8. Reber, L. L., Marichal, T., Galli, S. J. (2019). New models for analyzing mast cell functions in vivo. Trends in Immunology, 40(4), 361-373.
9. Sathish, V., Thompson, M. A., Bailey, J. P., Pabelick, C. M., Prakash, Y. S., Sieck, G. C. (2020). Electrostatic atomization-based pulmonary administration of ovalbumin in mice: development of a novel in vivo asthma model. Journal of Aerosol Medicine and Pulmonary Drug Delivery, 33(2), 98-110.
10. Yan, X., Zhang, Y., Wang, L., Chen, H., Wang, J., Gao, J., & Zou, X. (2020). Plumbagin alleviates airway inflammation in ovalbumin-induced asthma mice through suppressing the activation of nuclear factor kappa B and mitogen-activated protein kinases. Journal of Immunology Research, 2020, 1-13.
11. Zhang, Y., Tang, H., Cai, L., Zhao, J., Liu, X., Yao, D., … & Zhang, H. (2021). Nanoparticle-based targeted delivery of ovalbumin to dendritic cells for enhanced cellular immune response and asthma therapy. Journal of Materials Chemistry B, 9(19), 4072-4081.

Drug metabolism and pharmacokinetics (DMPK) are essential to understanding important characteristics of drug candidates, including absorption, distribution, metabolism, excretion, toxicity (ADMET), and pharmacokinetic (PK) properties. DMPK studies are conducted at the preclinical and clinical stages as well as post-approval. Preclinical DMPK studies involve both in vitro studies to evaluate drug candidate characteristics such as protein binding affinities and interactions with transporters and enzymes as well as in vivo analyses to assess toxicity and pharmacokinetics such as half-life, bioavailability, excretion, absorption, and distribution in preclinical animal models. Drug characteristics are further evaluated during clinical trials, including assessment of safety, dosage, side effects, efficacy, and drug-drug interactions (DDIs) in human participants. Post-approval studies involve preparing labeling restrictions for the market as well as collecting safety and effectiveness data in larger populations once available. 

Nearly 90% of drug candidates fail after entering clinical trials.  This high failure rate at late stages in the drug development pipelines results in wasted time and resources that could have been utilized for more promising candidates. In a 2016 estimation from the Tufts Center for the Study of Drug Development, each approved drug has an estimated price tag of $2.87 Billion ($3.65 Billion in 2022 dollars). The main driving factor for this high cost is the failure rate for other products. Analyses have revealed that the top reasons for drug candidate failures between 2010 and 2017 from the largest pharmaceutical companies were:

1. Lack of clinical efficacy (40-50%)
2. Unmanageable toxicity (30%)
3. Poor drug properties (10-15%)
4. Lack of market/commercial strategy (10%)

Proper preclinical DMPK studies can address the second and third most frequent causes of attrition: unmanageable toxicity and poor drug properties. Combined, these account for 40-45% of all drug failures. Identifying these characteristics earlier in the drug development pipeline could cut costs for pharmaceutical companies and shorten the time to effective therapeutics for patients. The risk is even higher for smaller companies. Smaller biotech companies tend to pursue riskier drug candidates, which are critical for innovative therapies, but when combined with limited resources and experience for conducting proper DMPK studies, contribute to a high rate of attrition.

A variety of DMPK techniques can be used to assess the preclinical toxicology of drug candidates. Toxicity is temporal, with the potential for both acute and chronic effects. Proper in vivo preclinical toxicology studies can evaluate the acute effects of multiple dosing strategies as well as long-term effects such as carcinogenicity or impacts on reproductivity. Toxicology studies may evaluate any metabolites that might form or transcriptional changes that result from administration and may indicate toxicity based on previously characterized compounds. By using multiple species for toxicity studies, investigators can choose species that have similar metabolic profiles to humans, allowing for more relevant comparisons.  

Poor drug properties such as absorption, distribution, metabolism, excretion (ADME), or pharmacokinetics account for 10-15% of drug attrition. Fifty years ago, these poor drug properties accounted for nearly 40% of candidate attrition. The progress of DMPK scientists in assessing these characteristics has come a long way in that time. These measurements can be obtained via in vitro assays with human-derived cells or tissues as well as in vivo animal studies. Two of the approaches currently used to predict human PK include allometric scaling and in vitro-in vivo extrapolation. Allometric scaling is used to predict human PK by relating in vivo-derived parameters collected in animal models. In vitro-in vivo extrapolation is an estimate of metabolic clearance by measuring the clearance in human cells or tissue in vitro and then scaling up.  

Twenty years ago, the focus of many DMPK studies for pharmaceuticals was primarily to characterize the kinetic properties of drug candidates for clinical trial design and regulatory registration. Since then, the field has shifted dramatically with new analyses including pharmacogenetics, pharmacogenomics, drug-drug interaction (DDI) predictions, and measurements of asymmetric organ or tissue exposure based on the organ-specific expression of drug transporters and metabolizing enzymes. 

In 2020, the FDA released updated guidance regarding DDI evaluation for drug candidates. These guidelines outlined in vitro experimental conditions as well as details for model-based DDI prediction strategies. Preclinical DDI studies are used for the design of trials to inform participant recruitment as well as for generating label restrictions and guidance post-approval. 

Pharmacogenomics is an emerging field of DMPK that evaluates the accumulative effect of genetic variants on drug responses and efficacy.  Genetic polymorphisms in genes that encode metabolizing enzymes or transports can vastly affect the pharmacokinetic properties of a given drug as well as how patients respond to therapy.  These biomarkers can affect dosing, and risks associated with the therapy, both important for labeling guidance and restrictions. They can also impact trial design and endpoints.  The FDA pharmacogenetic biomarkers in drug labeling list contains FDA-approved drugs with known pharmacogenomic biomarkers that affect the therapeutic response.  

Proper design and execution of DMPK studies can reduce drug candidate attrition, cut costs, and conserve resources for the most promising drug candidates. Smaller biotech companies often lack the resources to conduct robust DMPK studies, making it even more important to outsource these studies to a CRO with extensive experience and validated models. Because no individual model is a perfect comparison to humans, in vivo DMPK studies can be conducted in multiple models or species to compare ADMET properties across species. PharmaLegacy has an extensive set of preclinical animal models (> 600 validated models) to conduct DMPK studies from multiple species, including non-human primate models, with the capacity to run more than 200 concurrent animal studies. Scientists at PharmaLegacy also have years of experience performing DMPK/ADMET studies to help speeding up your drug discovery effort, minimizing toxicity liabilities, and ultimately reducing attrition rate in the clinic. PharmaLegacy can meet your company’s DMPK needs while remaining compliant with all applicable regulatory agencies.  

See the difference proper DMPK studies from PharmaLegacy can offer your company.

References

1. DiMasi JA, Grabowski HG, Hansen RW. Innovation in the pharmaceutical industry: New estimates of R&D costs. J Health Econ. 2016 May;47:20-33. doi: 10.1016/j.jhealeco.2016.01.012. Epub 2016 Feb 12. PMID: 26928437.
2. Dowden H, Munro J. Trends in clinical success rates and therapeutic focus. Nat Rev Drug Discov. 2019 Jul;18(7):495-496. doi: 10.1038/d41573-019-00074-z. PMID: 31267067. 
3. Sun D, Gao W, Hu H, Zhou S. Why 90% of clinical drug development fails and how to improve it? Acta Pharm Sin B. 2022 Jul;12(7):3049-3062. doi: 10.1016/j.apsb.2022.02.002. Epub 2022 Feb 11. PMID: 35865092; PMCID: PMC9293739.
4. Lai Y, Chu X, Di L, Gao W, Guo Y, Liu X, Lu C, Mao J, Shen H, Tang H, Xia CQ, Zhang L, Ding X. Recent advances in the translation of drug metabolism and pharmacokinetics science for drug discovery and development. Acta Pharm Sin B. 2022 Jun;12(6):2751-2777. doi: 10.1016/j.apsb.2022.03.009. Epub 2022 Mar 17. PMID: 35755285; PMCID: PMC9214059.
5. Tremaine L, Brian W, DelMonte T, Francke S, Groenen P, Johnson K, Li L, Pearson K, Marshall JC. The role of ADME pharmacogenomics in early clinical trials: perspective of the Industry Pharmacogenomics Working Group (I-PWG). Pharmacogenomics. 2015 Dec;16(18):2055-67. doi: 10.2217/pgs.15.141. Epub 2015 Nov 30. PMID: 26616152; PMCID: PMC5558530.

If you’ve been keeping up with the latest advancements in cancer research, you might come across the usage of humanized mouse models as a promising tool in cancer management and treatment.

This trend is driven by advances in the development of new rodent models which enabled scientists to further investigate and harness the power of immunotherapies in fighting tumors by replacing the mouse’s immune system with a functioning human one, hence the term “humanized”.

But first, what is a humanized mouse model?

A humanized mouse model is established by modifying specific genes that render it immunodeficient, lacking T, B, and NK cells, and replacing them with human functioning immune cells. This model serves as a preclinical tool in biomedical research by receiving transplantation of human tumor tissue known as “xenograft” derived from the patient’s cell line to explore cancer’s pathogenesis and evaluate different therapeutic effects.

Here, we highlight three different types of humanized mice models that are used in immuno-oncology studies:

• Humanized (hu) CD34+ Mouse Models
• Humanized (hu) PBMC Mouse Models
• Knock-in Humanized Mouse Models

 

CD34+ humanized mouse models are preferably used in long-term oncology studies.

Due to their ability to stably ingraft with huCD34+ hematopoietic stem cells, and their capacity in producing multi-lineage human immune cells that are viable up to nine months post-production, severely immune-deficient mice are exposed to whole-body irradiation followed by the injection of human CD34+ cells, this process makes the models ready for tumor implantation.

 

PBMC humanized mouse models are cost-effective in short-term oncology studies.

Because of their rapid engraftment with human immune cells, humanized PBMC mouse models are used in studies that aim to evaluate compounds for T cell immune modulation. This is done post the intravenous engraftment of human peripheral blood monocyte cells (PBMCs) in severely immune-deficient mice before or following the implantation of the xenograft.  This allows for quick evaluation of a novel immuno-therapeutic with human, specifically with a focus on T cell immunology. From study planning to start, PBMC models can be accomplished is just a few weeks.     This makes the model well suited for rapid results. However, PBMC models are limited in duration by GVHD onset within 4 to 8 weeks.  For longer duration models, CD34+ humanized models are a better choice.

 

Knock-in humanized mouse models offer a distinctive anti-tumor response in research.

By expressing chimeric proteins made of a humanized extracellular domain, knock-in mouse models with fully functioning immune systems are primarily used to evaluate the anti-tumor response of the immune checkpoint inhibitors related to human targets.  First generation humanized mice broadly supported human T cell engraftment. Recent advances permitted the addition of human cytokines such as GM-CSF, IL-3 and/or IL-15 creating 2^nd generation humanized mice models. Second, generation mice support an even more completed human immune system with increase in the engraftment of granulocytes, macrophages, NK and dendritic cells.

Regardless of 1^st or 2^nd generation model type, humanized mice models have the capacity of bearing both the human immune system and human tumors, but their successful engraftment of human immune cells depends strongly on the immunodeficiency of the recipient mice.

While ectomy procedures, radiotherapy, and chemotherapy remain the most effective methods for treating tumors, the five-year survival rate post-operation remains insufficient. The significant progress in onco-immunology enabled immunotherapy to attack a tumor by potentiating functioning lymphocytes instead of killing it directly which marked the forward leap in cancer treatment.

In addition, recent studies demonstrated that humanized mouse models opened new perspectives in immunotherapy by bearing both human immune cells and human tumors. This is translated through the model’s ability to be engrafted with tumors either in a form of cell-line-derived xenograft (CDX) or patient-derived xenograft (PDX), with the later method being extensively used in cancer research today. Even though CDXs consume less time, studies showed that in vitro culture, a step before engraftment may cause a substantial loss of features in primary tumors. PDXs on the other hand, are fragments of fresh human tumors engrafted directly onto the recipient mouse model which makes them challenging to establish and may lead to potential loss of their associated human stroma over time.

Using humanized mouse model as a preclinical application for cancer immunotherapies requires the reproduction of the tumor microenvironment (TME) in the hu-PDX mice model. TME comprises varying elements such as blood vessels, lymph vessels, stromal cells, immunocytes, fibroblasts, and the extracellular matrix (ECM). The establishment of this complex milieu is a dominant factor in oncobiology studies as it not only offers the environment for tumor development and metastasis but also aids in its diagnosis, prevention, and prognosis. Due to its major role in tumorigenesis and cancer development alongside the interplay between immunocytes and tumor cells post mice humanization and PDX implantation, TME can provide new strategies for future therapy.

Pairing humanized mice with an accomplished flow cytometry core is essential to understand the TME. Pharmalegacy (PL) is fortunately to have an excellent cytometry core with multiple cytometers supporting up to 16 color staining.   If you need to study T cell exhaustion markers, or a specialized subset of DC1 cells, PL can design a FACS panel to track all your cell populations of interest.

Additionally, the usage of humanized mice model to engineer genetic-modified T cells was reported to be of beneficial value in cancer patients receiving adoptive cellular therapy (ACT) which denotes expanding immunocompetent cells in vitro followed by reinjecting them back to the patients. The procedure of ACT infusion is based on T cells engineered to express transgenic T cell receptors (TCRs) or chimeric antigen receptors (CARs), which aids in improving the affinity with tumor-associated antigens (TAAs).

Also, a humanized mouse model was helpful in immune checkpoint blockade therapy. Several signaling pathways and inhibitory receptors grouped under immune checkpoints like programmed cell death protein-1 (PD-1), cytotoxic T-lymphocytes-associated protein-4 (CTLA-4), lymphocyte activation gene-3 (LAG-3), and T cell immunoglobulin-3 (TIM-3), all suppress excessively activated T cells preventing a self-tissue attack, hence eliminating the occurrence of autoimmune effects. The blockage of some immune checkpoints was marked as a unique setup in cancer treatment when PD-1 and CTLA-4 inhibitors won the Nobel Prize in physiology and medicine in 2018. The remarkable superiority of the humanized mice model in studying immune checkpoint inhibitors was established to test the effectiveness of individual clinical consultations for cancer patients.

First generation humanized mice have been highly predictive of human clinical success for check point therapies. Next generation of immune-oncology therapies will target processes beyond check point blockade. Future therapies will require a more complete TME that includes additional immune cell types commonly found in ‘cold’ tumors that do not respond to check point treatment. Second generation humanized mice promise to be the models of the future. Specifically, therapies that target NK cells, MDSC, and TAM can all benefit from 2^nd generation humanized mice.

Current studies are undergoing tremendous efforts to ensure the reliable usage of humanized mouse models as a representative tool in preclinical immune-oncology studies by tackling its major setbacks. At PharmaLegacy, we understand that the need for humanized models is of utmost importance; This is why our team of experts are always hard at work to provide you with reliable and cost-effective models that fit your studies.  Additionally, we manufacture our own humanized mice. This allows for customization to meet our client’s needs. We can transfect lentivirus expressing cytokines, screen donor CD34 stems cells, or additionally customize the model systems based on our customer’s needs.