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| EDITORIAL |
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| Year : 2023 | Volume
: 55
| Issue : 2 | Page : 71-75 |
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Do alternatives to animal experimentation replace preclinical research?
Vidya Mahalmani1, Ajay Prakash2, Bikash Medhi2
1 Department of Pharmacology, Jawaharlal Nehru Medical College, KAHER, Belagavi, Karnataka, India
2 Department of Pharmacology, PGIMER, Chandigarh, India
| Date of Submission | 17-Apr-2023 |
| Date of Decision | 27-Apr-2023 |
| Date of Acceptance | 08-May-2023 |
| Date of Web Publication | 03-Jun-2023 |
Correspondence Address:
Bikash Medhi
Department of Pharmacology, PGIMER, Chandigarh - 160 012
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/ijp.ijp_223_23
How to cite this article:
Mahalmani V, Prakash A, Medhi B. Do alternatives to animal experimentation replace preclinical research?. Indian J Pharmacol 2023;55:71-5 |
Preclinical research involving animals has been the gold standard for decades and is an important criterion for determining the safety and efficacy of products before they are brought to market.
The main aim of preclinical research is to determine a compound's safety profile. Toxicity testing of the novel compound involves animals. This allows researchers to determine the safe dose of the drug that is further used to carry out clinical trials in humans.
Data collected from preclinical research are important to ascertain the safety of clinical trials. The most common species used for preclinical research is a rodent and nonrodent species. However, most of the drug candidates fail when they reach clinical trials.
However, animal experimentation for scientific research has raised concern among animal welfare groups for a long time. In 1975, the Societies for Protection and Care of Animals started an initiative worldwide that raised its voice against animal research.[1]
The Committee for Control and Supervision of Experiments on Animals under the Government of India has set guidelines for care and use of animals in research. At the institutional level, the Institutional Animal Ethics Committee takes care of ethical issues pertaining to care and animal handling. Animal lovers have been opposing animal experimentation to ensure the safety of animals. Preclinical experiments and toxicity testing in animals have been challenged because of the poor correlation of results obtained from clinical trials.[2]
In addition, animal care, the cost involved in procuring them, maintenance of the animal house, and suitably trained staff are some of the economic considerations that pose a huge burden for preclinical experiments.
| » The Fallacy of Preclinical Drug Development | |  |
Validation of a model is a prerequisite in drug discovery and development. A combination of preclinical models would be preferred rather than just using a single model as it fails to fulfill all the criteria of a clinical scenario. As the sample size of preclinical studies is quite less compared to clinical trials, the disparity can occur on extrapolation of the results.
Therefore, it is not possible to generalize results to clinical settings. Differences between the physiology and genetic makeup vary between species, which can lead to variability in pharmacokinetics. Another important drawback of preclinical studies is genetic heterogeneity which is very difficult to model in animals. Majority of the animals used in preclinical studies are probably identical in contrast to humans and are performed under standard conditions that fail to mimic a clinical condition.[3]
The TGN1412 trial is an example where the preclinical model could not be entirely translated into the clinical trial. This drug is a humanized anti-CD28 monoclonal antibody that was evaluated for treating various immunological conditions such as multiple sclerosis, rheumatoid arthritis, and cancers. TGN1412 did not show any toxic effects when tested on different animals. However, using a subclinical dose that was 500 times less than the dose found safe in animal studies leads to fatal systemic organ failure in humans.[4]
In December 2019, a clinical trial of inarigivir in chronic hepatitis B was halted because of the tragic death of the patient. Evidence from preclinical studies demonstrated the safety and efficacy of this drug.[5]
For a drug to be approved by the US Food and Drug Administration (FDA), toxicity tests are required in rodent and nonrodent species. Thousands of animals are used to perform such tests. In spite of this, only nine among ten drug candidates fail to show promising results when they enter clinical trials. Hence, there is rising concern regarding the predictive value of preclinical studies. FDA is now focusing on 3 Rs. to reduce the utilization of animals in preclinical studies: replacement, reduction, and refinement.
| » Can Modern Technology Completely Replace Animal Testing? | | |
With the advancement in technology, the use of “alternatives” for preclinical studies is of utmost priority these days. Modern technology has paved the way for several alternative models to animal research that are comparatively less time-consuming.
Human-based computer models can be less time-consuming and curb the need to translate results. Early anticipation of toxicity in humans is important in reducing the expenses of drug development.
In silico modeling has been given much importance in preclinical evaluation. The advantage of in silico modeling is that faster predictions can be made for a huge set of compounds by high throughput mode. In addition, predictions can be made based on the structure of compound even before it has been synthesized. Computational approaches do not completely replace animal research. Nevertheless, the rate of preclinical drug development can certainly be expedited and also reduce the time and cost incurred during animal studies. In silico models also have the ability to recognize areas for repositioning of drugs as well as for redirecting drugs that have proven inefficacious for certain indications but can be introduced again for another indication.[6]
In 2016, the European Union funded the CompBioMed Project with an intent of creating a whole in silico humans for testing drugs, disease modeling and to develop personalized therapy.[7]
Tissue engineering has made it possible to design three-dimensional (3D) tissue constructs using human cells. Therefore, the activity in an engineered human tissue will probably be able to predict the outcomes in humans in a better way.
Tissue engineering models mimicking urothelium, corneal epithelium and stroma, oral mucosa, and vaginal mucosa of humans have been designed.[8]
3D constructs of cardiac muscle permit the computation of virtual variables such as heart function, kinetics, twitch force, rhythm, and rate. These constructs can be used as a research tool, as they can be used for toxicity testing and disease modeling and replaced preclinical toxicity testing.[9],[10]
Truitt et al. worked on a 3D cardiac microtissue model to distinguish the mechanism of action of sunitinib that causes human toxicity, a drug with substantial cardiotoxic potential used in the treatment of renal cell, gastrointestinal tumors.[11]
[Figure 1] depicts various alternatives to preclinical research.
However, pharmaceutical industries have been slow to implement such technologies due to a lack of regulatory measures so as to how these models can be integrated with preclinical and clinical trials. Tissue culture has got certain limitations while conducting preclinical studies in predicting drug toxicity as these cells fail to retain their morphology and maintain their original cellular function. Tissue culture cells lack complex environments like the cells in vivo, where they are subjected to sheer forces and stretching. In addition, one cannot test interactions between various organs in tissue culture.
To overcome this, microfabrication approaches and microfluid technology are merged with computer technology giving rise to a novel in vitro organ model called organ-on-chip (OC). This along with multiorgan chip interactions simulates whole-body responses known as “body-on-chip” (BC).
At Wyss Institute, Harvard University, OCs have been used to simulate interactions between different organs within a body.[12] The software enables researchers to control cell architecture, biochemical changes within chips, mechanical forces, and tissue-to-tissue interfaces. Researchers also showed that multi-organoid BC systems could identify hepatotoxicity and cardiotoxicity at human doses. These drugs had to be looked back at by FDA with respect to these adverse effects. The harsh reality was that all these drug candidates had failed to exhibit significant toxicity in preclinical and clinical studies. Researchers are investigating chip technology to assess the utilization of stem cells to figure out treatment options for myocardial repair and also to develop in vitro models for various cardiac diseases.
[Table 1] depicts the list of few drugs that passed preclinical research but exhibited liver toxicity in clinical trials. The chips tested for the same accurately predicted liver toxicity same as that of clinical studies.[13] | Table 1: List of drugs that passed preclinical research but failed in clinical trials
Click here to view |
Although FDA has highlighted the need for alternative methods, till date, animal testing is being performed in preclinical phases, and does not support the substitution of alternative methods.
In 2006, with the aim of lowering the usage of animals and supporting in silico methods, Registration, Evaluation, Authorization, and Restriction of Chemicals legislation was passed by the European Union.[14],[15]
Guidelines to restrict animal usage were also proposed by the European Medicines Agency.[16],[17],[18]
In 2019, FDA formed the Alternative Methods Working Group (Working Group), a platform that primed the public about the FDA's progress pertaining to the establishment and execution of alternative methods.
A committee “The Interagency Coordinating Committee on the Validation of Alternative Methods” was set up by the U. S. government to encourage the development, validation, and regulatory acceptance of different technologies to reduce, replace, or refine the usage of animals in testing.
The FDA's Center for Tobacco Products encourages the adoption of alternative methods for toxicity testing. In vitro and in silico techniques are performed to deepen knowledge about tobacco-related toxicities.
Researchers from the Center for Drug Evaluation and Research have been working on liver microphysiological systems to assess their potential in testing drugs for hepatotoxicity and pharmacokinetics. Although it is a promising method, currently, there is a lack of sufficient scientific evidence to draw a definitive conclusion on whether they can replace animal testing.[19]
With the aim of bringing down the duration and expenditure of drug development, along with the decline in public support for animal testing, researchers are being compelled to unearth alternative methods for research. In late December 2022, President Joe Biden signed legislation, according to which new drugs do not require animal testing to obtain approval from the U. S. FDA.[20] The 2023 Consolidate Appropriations Act (H. R. 2617) incorporated a section on “modernizing” clinical trials. A portion of it on alternatives to animal testing, amends the existing law. According to the amendment, new drugs can now proceed onto clinical trials if they prove to be promising in “nonclinical tests,” which include technological advances such as computer simulations, 3D-printed body parts, and organ chips.[21]
However, some researchers opine that nonanimal alternatives are still “in their infancy” and cannot completely replace animal models as of now. Therefore, the shift away from animals will require action on the part of both drug makers and regulators. Funding is also required for developing and validating the alternatives. Currently, very few methods have been approved by federal regulators. Various government agencies and countries should join FDA in its effort to bring a change in the current system.
| » Conclusion | | |
Conventionally, animal models are typically used to produce nonclinical proof-of-concept data of the target optimization and validation for the efficacy of new active pharmacological ingredients (APIs). This in vivo step of the drug discovery process is an important step in finding out the efficacy and safety of APIs in the complete biological system. In order to promote drug development programs in an ethical way, regulatory bodies have even encouraged to use animal models in safety and toxicity studies under good laboratory practice conditions and allow data on at least two species for the learning of biological variabilities. The disease modeling of animals may provide a more accurate predictor of probable harmful human outcomes than the in vitro setting.
As per the new U. S. FDA, the Act (H. R. 2617) incorporated a section on “modernizing” clinical trials through alternatives to animal testing by using computer simulations, 3D-printed body parts, and organ chips. However, there is a need for detailed deliberation among the scientific community because invivo and in vitro systems may not be completely extrapolated as they create an artificial environment through technologies. Most of the biological variations are still in use and getting explored. Hence, the need for animal experimentation in the screening of new APIs may not be completely replaced by the in vitro system. Therefore, need to understand the role of developing new ideal animal models for more reliable results for pharmacodynamic data, safety or toxicity data, and the extrapolation of first in human dose to accelerate clinical trials.
| » References | | |
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| 10. | Nugraha B, Buono MF, von Boehmer L, Hoerstrup SP, Emmert MY. Human cardiac organoids for disease modeling. Clin Pharmacol Ther 2019;105:79-85. |
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| 12. | Wysse Institute for Biologically Inspired Engineering, Harvard University. Available from: https://wyss.harvard.edu. [Last accessed on 2020 Mar 22]. |
| 13. | Jang KJ, Otieno MA, Ronxhi J, Lim HK, Ewart L, Kodella KR, et al. Reproducing human and cross-species drug toxicities using a Liver-Chip. Sci Transl Med 2019;11:eaax5516. |
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[Figure 1]
[Table 1]
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