Modernizing Toxicology Practices on Biologics - Essay Example

College

Modernizing Toxicology Practices on Biologics 

Problem Statement

Recent research has focused on identifying the effective approaches to the product development of drugs, new medications, and other medical devices. The current product development process registers remarkable costs and minimal success rates. Additionally, toxicological tests have proven ineffective in determining the potential adverse effects of new drugs. For this reason, there is a need to develop new approaches that can help in determining whether new medicines will register undesirable adverse effects. Previously, the toxicology department had been using in vivo animal studies as the gold standard in determining the effectiveness of new drugs and predicting their ability to register adverse drug reactions (Borgert, Wise, & Becker, 2015). Preclinical testing of new medications has a critical role because it helps in determining some of the potential risks that the new drug may register upon administration. For this reason, there is a need for toxicology tests to be as effective as possible.

For a long time, toxicology testing has been relying on animal models administered with the maximum tolerated doses. In the extrapolation of such results to human beings, the reduction of doses has been the order of the day (Coleman, 2006). Unfortunately, the use of these animal models does not provide specific results of how the potential drugs will affect humans. As a result, there is a need to increase the safety of patients by adopting a paradigm shift that will alter the approaches used in toxicological testing. Moreover, there is an evident need for scholars to increase knowledge concerning the relevance of in vitro studies that can determine the effectiveness of drugs in humans (Piersma, 2017). In the past, toxicologists have been relying on a single approach to the determination of the adverse effects of potential drugs. Undoubtedly, it is explicit that a universal approach cannot register the expected benefits in carrying various assays. Technological advances should serve as a major driver in the development of effective approaches to toxicology testing.

Supporting Data

Uncertainty in drug toxicology testing has proven to be a challenge when determining the safety of potential drugs. The use of animal models does not provide specific data concerning the adverse effects of drugs or the specified dosages to be used in humans (Piersma, 2017). Particularly, many of the existing tests are unable to ascertain the level of safety that a certain drug registers. The reliance on in vivo toxicology testing has proven ineffective in accurately predicting some of the adverse reactions associated with a drug (U.S. Food and Drug Administration, 2016). The in vivo drug testing assays rely on animals used for testing purposes. Increasing the effectiveness of toxicology tests is of critical importance in promoting the safety of humans. Specifically, effective toxicology testing will help in understanding whether a drug can register adverse drug reactions that are beyond control.

There is a great emphasis on the need to embrace in vitro approaches that will help toxicologists to easily determine the potential risks and harms associated with a certain drug. The most important aspect is to ensure that toxicologists embrace approaches that register high levels of accuracy, limited costs, and are not time-consuming. There is a need to develop effective drugs that will help patients to register positive health outcomes. In vitro studies present a significant percentage of relevance to humans compare to the in vivo studies (Coleman, 2006). With the uncertainties associated with the traditional toxicology models, there is a need to put in place rigorous approaches that help in determining the underlying adverse events. In the past, there has been limited knowledge concerning toxicity mechanisms. Currently, more scholars have exhibited the need to gain a deeper understating of the toxicity mechanisms and pathways.

Undoubtedly, it is possible to develop better models that help in understanding the adverse responses that occur in humans after the administration of certain drugs. The existing models are unable to register the expected levels of rigor in predicting the occurrence of adverse drug events. The use of animals in previous studies has been highly condemned as one of the unethical procedures in the toxicology department (Borgert, Wise, & Becker, 2015). As a result, it is better to develop animal models that will be able to predict the potential occurrence of different adverse events accurately. For this reason, modernizing toxicology testing will lead to the development of relevant animal models that can help in the identification of the adverse events and comorbidities associated with various diseases.

Traditional approaches in toxicology testing have not been able to consider the molecular targets as well as the host genetic factors associated with the reported adverse events. Modernizing this approach will focus on fully characterizing the molecular targets as well as host genetic factors that may be responsible for different adverse events. Additionally, the modernization of approaches used in toxicology studies will involve the identification of biomarkers that toxicologists can use in determining the perceived risk of certain drugs (Piersma, 2017). Biomarkers can help in monitoring the performance and functioning of various drugs in various organs. It is possible to include quantitative imaging as a potential approach to monitoring the biomarkers.

Traditional approaches did not involve the use of modern technology. However, recent technological advances have highlighted the need for embracing computational methods for use in toxicology testing. Computational methods will allow the toxicologists to make use of simulation models that can recreate drug interactions as well as patient characteristics (U.S. Food and Drug Administration, 2016). Other computational methods include the adoption of computer-generated models that represent the functioning of various cells, organs, and entire systems. After a critical consideration of the traditional approaches used in determining the risk of adverse events, it is clear that there is a need to bring on board new data mining approaches that can fasten the process. The use of chemical structures generated by computers can significantly increase the analysis of the drug’s mechanism.

In the past, toxicologists have been relying on traditional approaches without the integration of various dimensions in toxicology testing. However, modern technology provides a great opportunity that toxicologist can use in increasing the level of certainty when conducting toxicology tests. Undoubtedly, the application of computational methods will represent a major shift from the traditional approaches to the modernized strategies of conducting toxicology testing. Technological advances have become extremely popular in the twenty-first century(Piersma, 2017). For this reason, the lack of modern technology is no longer an obstacle in the modernization of toxicology testing. The main challenge is to select the best approaches that will improve the toxicology testing and help in reducing unwanted adverse events (Coleman, 2006). Different technological industries have made progress in the development of biochemical assays, cellular assays, and in vitro models that are likely to register better outcomes in toxicology testing. The adoption of silico methods is also a possibility in the modern day and can serve to register positive outcomes in toxicology testing.

Underrating the significance of effective toxicology testing is impossible. When the process is effective, it is possible to promote patient safety after the exposure to certain chemical substances. Failure to conduct successful toxicology testing will compromise the safety of patients who will take the medications. The most important aspect is ensuring that through the modernization of the toxicological testing process, more positive outcomes are evident. The determination of effective models and approaches for toxicology testing will require the formation of partnerships with different stakeholders such as pharmaceutical companies, National Institutes of Health, and interested agencies (Borgert, Wise, & Becker, 2015). Toxicology represents a regulatory science that has different interested agencies and pharmaceutical companies. These agencies and companies need to come together and discuss the potential of embracing new approaches that will register desirable outcomes. The formation of partnerships with various agencies will provide a better platform to analyze the relevance of each model critically.

Undoubtedly, partnerships can be extremely useful in helping the toxicology department to embrace the best approaches. The shift from traditional to modern approaches will register certain challenges for the toxicology department. For this reason, the collaboration of partners will enable the department to address the challenges and move forward successfully. In the twenty-first century, improving and modernizing toxicology testing approaches will also include the development of a reliable toxicity data (Piersma, 2017). The use of traditional methodologies has not allowed the toxicology department to establish a remarkable database that highlights the tested toxicities of various substances. It is time for the toxicologist to pursue the approaches that are easier to implement as they focus on investing in more expensive technology. The combination of these approaches will have a significant impact on the toxicology testing.

Many of the new approaches will be able to register a measure of certainty regarding the safety of different drugs. Unfortunately, there will be a need for technological expertise in the use of the modern approaches to enhance toxicology testing. Moving from traditional approaches to globally recognized models for toxicology testing is likely to have an overall impact on patient safety. The success in modernizing toxicology testing will help government agencies to approve substances that do not register undesirable adverse effects. The government agencies will have better and reliable data to ascertain the safety of different drugs (U.S. Food and Drug Administration, 2016). On the other hand, companies will be able to develop safer and reliable drugs and chemical agents. Consumers will have more confidence in using various drugs since they recognize the effectiveness of the modern technology. Currently, different agencies such as National Institutes of Health have established platforms for working together towards modernizing toxicology testing.

Conclusion

There is a need to adopt better models in the determination of potential adverse effects associated with drugs. Toxicologists need to gain a deeper appreciation of the toxicity mechanisms through in vitro ad in vivo studies (Coleman, 2006). The adoption of potential markers in such studies will help in increasing the knowledge associated with toxicity mechanisms. The adoption of bioinformatics and computational methods will help researchers to register remarkable progress in toxicology testing (U.S. Food and Drug Administration, 2016). Other advances in biology and genomics will aid in increasing knowledge concerning the adverse effects associated with different drugs. Implementing these new approaches ill help scientists to understand the specific adverse effects that different drugs may trigger.

There is a great emphasis on the need to embrace in vitro approaches that will help toxicologists to easily determine the potential risks and harms associated with a certain drug. The most important aspect is to ensure that toxicologists embrace approaches that register high levels of accuracy, limited costs, and are not time-consuming. There is a need to develop effective drugs that will help patients to register positive health outcomes. In vitro studies present a significant percentage of relevance to humans compare to the in vivo studies (Coleman, 2006). With the uncertainties associated with the traditional toxicology models, there is a need to put in place rigorous approaches that help in determining the underlying adverse events. In the past, there has been limited knowledge concerning toxicity mechanisms. Currently, more scholars have exhibited the need to gain a deeper understating of the toxicity mechanisms and pathways.

Undoubtedly, it is possible to develop better models that help in understanding the adverse responses that occur in humans after the administration of certain drugs. The existing models are unable to register the expected levels of rigor in predicting the occurrence of adverse drug events. The use of animals in previous studies has been highly condemned as one of the unethical procedures in the toxicology department (Borgert, Wise, & Becker, 2015). As a result, it is better to develop animal models that will be able to predict the potential occurrence of different adverse events accurately. For this reason, modernizing toxicology testing will lead to the development of relevant animal models that can help in the identification of the adverse events and comorbidities associated with various diseases.

Traditional approaches in toxicology testing have not been able to consider the molecular targets as well as the host genetic factors associated with the reported adverse events. Modernizing this approach will focus on fully characterizing the molecular targets as well as host genetic factors that may be responsible for different adverse events. Additionally, the modernization of approaches used in toxicology studies will involve the identification of biomarkers that toxicologists can use in determining the perceived risk of certain drugs (Piersma, 2017). Biomarkers can help in monitoring the performance and functioning of various drugs in various organs. It is possible to include quantitative imaging as a potential approach to monitoring the biomarkers.

Traditional approaches did not involve the use of modern technology. However, recent technological advances have highlighted the need for embracing computational methods for use in toxicology testing. Computational methods will allow the toxicologists to make use of simulation models that can recreate drug interactions as well as patient characteristics (U.S. Food and Drug Administration, 2016). Other computational methods include the adoption of computer-generated models that represent the functioning of various cells, organs, and entire systems. After a critical consideration of the traditional approaches used in determining the risk of adverse events, it is clear that there is a need to bring on board new data mining approaches that can fasten the process. The use of chemical structures generated by computers can significantly increase the analysis of the drug’s mechanism.

In the past, toxicologists have been relying on traditional approaches without the integration of various dimensions in toxicology testing. However, modern technology provides a great opportunity that toxicologist can use in increasing the level of certainty when conducting toxicology tests. Read More