Biomedical Science Assignment: Evaluation Of Chronic Myeloid Leukemia
Over the course of the module tutors will challenge you with case-based learning, protocols and mockdata. In addition to developing theoretical understanding of the core biomedical science disciplines, you are required to complete risk assessments and control of substances hazardous to health(COSHH) forms. You will develop and understanding of ethical implications, data protection and professional laboratoryconduct. You are required to consider quality control (QC) measures, reproducibility and accuracy of data and stepstaken if there is a QC failure.
The format of the professional skills log developed in this biomedical science assignment will include reports based on each of the topics undertaken:
Microbiology approx. 720words
The report on biomedical science assignment detailed the core theoretical concepts of biomedical and develops an understanding of COSHH. It also outlined the ethical conducts of biomedical practices and laboratory regulations. The quality control measures are also considered and detailed in this professional log.
Overview of Chronic Myeloid Leukemia
Cancer is a disease in which cells begin to divide uncontrollably and can change from one source to another. Any cell from any part of the body can become cancerous and move to other parts of the body. Chronic Myeloid Leukemia (CML) is a type of cancer that occurs from cells (specifically blood-forming ones) in the bone marrow. It is also known as chronic leukaemia in the blood vessels. CML occurs when randomized gene expression occurs with immature differentiation of myeloid cells. Myeloid cells are pre-existing cells that makeup cells (red blood), cells that produce platelet (megakaryocytes), and many types of cells like white blood-producing ones (other than lymphocytes). This mutation leads to the formation of an unusual type of union due to the interaction between chromosome 9 and chromosome 22. BCR-ABL is a type of gene, which converts a cell into a CML cell. Leukaemia cells build up and proliferate in the bone marrow, causing new metastatic lesions in various body parts that shed blood. CML is cancer that is mainly slow-growing, but it can turn into very severe leukaemia, which is difficult to treat (The American Cancer Society, 2020).
Evolution of the disease and current clinical practices:
The treatment status of chronic myeloid leukaemia has changed dramatically in recent times. Most patients now enjoy a normal life span. The policy objective of treating patients with chronic myeloid leukaemia is to achieve a consistent cellular response (DMR) and discontinuation of non-medical therapies (DFR). The European Leukemia Net has called a team of experts to achieve this goal and to revise treatment plans from previous recommendations. According to European leukaemia, the first line of resistance to chronic leukaemia is Tyrosine Kinase Inhibitor (TKI) similar to Imatinib (Hochhaus et al., 2020). Imatinib is an inhibitor of tyrosine kinases, including PCR-APL, for the treatment of chronic myeloid leukaemia (CML). By inhibiting the selective activity of targeted proteins involved in cell proliferation. This may help to monitor the wild-type function and the functional activation of the C-kit tyrosine kinase. The close association between in vitro responses of IFNalpha and imatinib suggested that it could be an alternative form of IFNalpa treatment for the chronic CML phase. Imatinib has beneficial effects on IFNalpha treatment that can be administered orally. For Futmoremore, PCR-APL-expressing cells are exposed to the treatment of imatinib and also receive scheduled cell death. Imatinib has also been implicated in the treatment of some cancers that express these kinases (Radford, 2002). Imatinib showed a selective PCR-APL1 kinase inhibitor with significant improvements in the prediction of patients with CML. The study, published in the prestigious NEJM journal, followed patients under Imadin treatment for more than a decade, with an average follow-up period of 10.9 years. In this open-label, multicenter testing, CML patients who are diagnosed earlier while in the chronic phase were most likely to be prescribed interferon-alpha or imatinib and citrate for overall survival, treatment response, adverse events, and adverse drug reactions. The patients who are treated with imatinib has a survival rate of around 83% for the last 10 years (in statistical mean). Around 48% of patients are assigned to and completed treatment with imatinib successfully, and most of these patients (82.8%) had a response of complete cytogenetic. Adverse severe events associated with imatinib were rare (Hochhaus et al. 2017). These clinical trials have shown that imatinib is safe in terms of adverse drug side effects and is highly effective in treating patients, which has led to an increase in total survival.
Clinical trials are a form of research performed on people with the target of evaluating a medical intervention. For researchers in the medical field, clinical trials are the primary way to investigate and deduce if a new treatment, like a new medical device or a new drug, is effective and safe for patients. A trial in clinical experiment or research usually aims to find whether a new treatment is more or less effective and whether it is more or less safe than the existing mode of treatment (National Institutes of Health, 2017). Clinical trials have four phases:
Phase I includes a small experimental treatment on a small group of healthy people usually between 20 to 80. The aim of phase I of the clinical trial is to check for any adverse effect of the treatment and also to find out the correct dosage for the usage of the drugs.
Phase II increases the cohort to about 100 to 300 people. Phase II of clinical trials deal with the effectiveness of the treatment in people with the disease along with acquiring data regarding the safety of the treatment (National Institutes of Health, 2017). This phase usually lasts several years.
Phase III trials gather data on both the safety as well as the efficacy of the treatment in a different population (race dependent) and different dosage or combination with other drugs. The sample population ranges between several hundred to a few thousand people. The outcome of this phase is required to be approved by competent authorities like the FDA.
Phase IV occurs after approval from authorities like FDA and occurs in a large and diverese3 population (National Institutes of Health, 2017).
Microbiology deals with the study of microorganism with may be unicellular, multicellular or cellular including bacteria, virus, fungi, archaea and other aspects. This branch of science includes the study of, biochemistry, cell biology, virology, ecology, evolution and physiology of microorganism and also the host response and interaction with these microorganisms. Medical microbiology, a part of microbiology which includes the immune system of the host (human) and the immune response of the host to the various microorganism including bacteria, virus, fungi etc. Clinical microbiology includes virology, mycology, parasitology etc. In the case of a clinical trial of a drug, the patient is studied for various reactions to the drug. Some treatment, especially those involving cancer therapy, surgery or new implants like pacemakers often leads to varied immune response (Breccia et al. 2011). The treatment can also the patient to be vulnerable to various pathogenic infections which are required to be studied for preventing any complications or to decide the general safety of the treatment for the patient. Imatinib which has been proven as the first line of defence against chronic myeloid Leukemia is safe in terms of the occurrence of opportunistic and viral infections. In a study with 250 patients under imatinib treatment for both early and late-stage chronic myeloid Leukemia it was revealed that in both cases, there was a similarly low incidence of opportunistic infections(bacterial or fungal) as viral infection (Breccia et al. 2011).
Hazard ratio can be described as the outcome of therapeutic trials where the aim is to determine to what extent a treatment can shorten the duration of illness without adversely affecting the host too much especially in cases of clinical trials of anti-cancer therapies.
Most clinical involves substance which may be hazardous to human health. The investigators are required to follow certain guidelines which are known as control of substances hazardous to health (COSHH) regulations. The COSHH regulations are a set of guidelines that regulates how various wastes developed in a clinical trial are disposed of (Russell, 2019). The waste products are segregated based on their nature (hazardous, non-hazardous) origin (anatomical waste, metabolic wastes, plastic wastes, glassware wastes and other various substances) and toxicity (toxic chemical, toxic non-chemical non-toxic chemical and other types of chemicals).
Bioinformatics is a subdivision of both biological science as well as computer science. This branch of study involves the acquisition, storage, analysis, and dissemination of various biological data including DNA and amino acid sequences. It acts as an interdisciplinary field that helps us to interpret biological data by developing various types of tools and software. It particularly plays pivotal roles in dealing with large and complex data sets. Clinical bioinformatics is a subset of bioinformatics that deals with clinical data sets like those generated during a clinical trial (Wang & Liotta, 2011). Bioinformatics (Clinical) plays a significant role in many applications related to clinical research, including the technology of omics (transcriptomics, genomics, metabolomics, and proteomics), signalling and metabolic pathways, discovery and development of biomarker, gene ontology, pharmacometrics, biology (computational), image analysis (high-throughput). Human Molecular Genetics, Tissue Bank (Human), Biology & Mathematical Medicine, Profiling & Systems Biology and Protein Expression. The term clinical bioinformatics can be explained and detailed as the bioinformatics and related technologies application in clinical research for properly understand the mechanisms of diseases at the molecular level and response to the disease by the host - with the potential therapeutic and treatment of the disease (Wang and Liotta, 2011).
Clinical research is an extremely long process involving the discovery and development of drugs followed by clinical trials to test the safety and efficacy of drugs. Drug discovery and development involve a long-drawn-out process, including goal identification, verification of identified targets, and ultimately optimization of leads received. Various bioinformatics technologies have been developed to aid research in this process such as simulation of molecular dynamics, molecular docking, the activity of quantitative structure & proteomics and relationship analyzer. In addition to accelerating the clinical research process, the advancement of bioinformatics has helped to develop new knowledge related to data management, and health & disease during clinical trials, and the clinical data usage for conducting the secondary research. Use of various software such as data capture both remote, and electronic and generating electronic case report form (eCRF) while conducting clinical trials to store data generated about drug safety, various adverse effects of the drug, opportunistic or viral infections. is done. Other physiological parameters respiratory rate, oxygen saturation, like body temperature, urine output, immune response, blood pressure, and others. There are other aspects like overall patient survival with disease-free and other various aspects. Bioinformatics helps to collect data and provide meaningful information derived from this large amount of produced data. . E-clinical is Oracle clinical software that is used for clinical data management and statistical analysis of data (Gill et al. 2016). Other bioinformatics tools can be used to calculate overall survival, disease progression, and disease-free survival using the Kaplan Myer curve. This specific framework is the best way to measure survival and disease progression in patients in a clinical trial (Kishore et al. 2010). By considering this framework or tool the probability of survival over a given period of time can help to overcome many small gaps.
Conclusion and knowledge understanding:
Clinical trials are the primary way for researchers to find whether a new drug or treatment plan is more effective with fewer or equal side effects to that of the existing treatment. Clinical trials involve a complete understanding of the physiology as well as the molecular and genetic aspect of the disease and the host response to the disease. Bioinformatic tools have evolved to help both in the screening process in the pre-clinical trial phase as well collating the data obtained during the clinical trial phase in a meaningful and coherent way. Clinical microbiology is another aspect of a clinical trial that lets investigators monitors the adverse effect of the drug in terms of immune system response, opportunistic and viral infection. And finally, all clinical trials need to adhere to COSHH regulations and guidelines to dispose of all hazardous waste generated during the whole research process.
Breccia, M., Girmenia, C., Latagliata, R., Loglisci, G., Santopietro, M., Federico, V., Petrucci, L., Serrao, A., Salaroli, A., & Alimena., G. (2011). Low Incidence Rate of Opportunistic and Viral Infections During Imatinib Treatment in Chronic Myeloid Leukemia Patients in Early and Late Chronic Phase. Mediterranean Journal of Hematology and Infectious Diseases, 3(1). https://doi.org/10.4084/MJHID.2011.021
Gill, S. K., Christopher, A. F., Gupta, V., & Bansal, P. (2016). Emerging role of bioinformatics tools and software in evolution of clinical research. Perspectives in Clinical Research, 7(3), 115–122. https://doi.org/10.4103/2229-3485.184782
Hochhaus, A., Baccarani, M., Silver, R. T., Schiffer, C., Apperley, J. F., Cervantes, F., Clark, R. E., Cortes, J. E., Deininger, M. W., Guilhot, F., Hjorth-Hansen, H., Hughes, T. P., Janssen, J. J. W. M., Kantarjian, H. M., Kim, D. W., Larson, R. A., Lipton, J. H., Mahon, F. X., Mayer, J., & Nicolini, F. (2020). European LeukemiaNet 2020 recommendations for treating chronic myeloid leukemia. Leukemia, 34(4), 966–984. https://doi.org/10.1038/s41375-020-0776-2
Hochhaus, A., Larson, R. A., Guilhot, F., Radich, J. P., Branford, S., Hughes, T. P., Baccarani, M., Deininger, M. W., Cervantes, F., Fujihara, S., Ortmann, C.-E., Menssen, H. D., Kantarjian, H., O’Brien, S. G., & Druker, B. J. (2017). Long-Term Outcomes of Imatinib Treatment for Chronic Myeloid Leukemia. New England Journal of Medicine, 376(10), 917–927. https://doi.org/10.1056/nejmoa1609324
Kishore, J., Goel, M., & Khanna, P. (2010). Understanding survival analysis: Kaplan-Meier estimate. International Journal of Ayurveda Research, 1(4), 274. https://doi.org/10.4103/0974-7788.76794
National Institutes of Health. (2017). What Are Clinical Trials and Studies? National Institute on Aging. https://www.nia.nih.gov/health/what-are-clinical-trials-and-studies
Radford, I. R. (2002). Europe PMC. PubMed, 3(3), 492–499. https://pubmed.ncbi.nlm.nih.gov/12054102/
Russell, J. (2019). The COSHH principles. Dental Nursing, 15(9), 456–458. https://doi.org/10.12968/denn.2019.15.9.456
The American Cancer Society. (2020). What Is Chronic Myeloid Leukemia? Cancer.org; American Cancer Society. https://www.cancer.org/cancer/chronic-myeloid-leukemia/about/what-is-cml.html
Wang, X., & Liotta, L. (2011). Clinical bioinformatics: a new emerging science. Journal of Clinical Bioinformatics, 1(1), 1–3. https://doi.org/10.1186/2043-9113-1-1