As a doctor who has treated the COVID patients, it makes me wonder whether the treatment modalities currently in use, continue to be used in future or there is an ocean of possibilities still unexplored. For this reason, I started to review articles more on the Use of Newer treatment Modalities like Immunomodulatorsin COVID, also can Artificial Intelligence (AI)help predict the future? Can AI help for evaluating the newer treatment modalities?
The World Stands a Still, the Pandemic has not ended yet. A new virus, a new strain, new vaccine, new treatment? Every day one highlighted news – When will the Coronavirus (COVID-19) go?
Novel coronavirus disease 2019 (COVID-19/ severe acute respiratory syndrome coronavirus 2 {SARS-CoV-2}) is a pandemic which has affected more than 145 million individuals globally. As on 23rd April,2021 India has more than 16 million reported cases of COVID-19 infection and 186,920 deaths attributed to COVID-19.
As a doctor who has treated the COVID patients, it makes me wonder whether the treatment modalities currently in use, continue to be used in future or there is an ocean of possibilities still unexplored. For this reason, I started to review articles more on the Use of Newer treatment Modalities like Immunomodulatorsin COVID, also can Artificial Intelligence (AI)help predict the future? Can AI help for evaluating the newer treatment modalities? Let us first understand about the way Coronavirus affects our body. Coronavirus is affiliated with higher concentrations of proinflammatory cytokines that lead to lung damage, which can then lead to, respiratory failure, severe acute respiratory distress syndrome and resultant increased mortality.Newer treatment Modality like Immunomodulatory therapy has the potential to inhibit cytokines and quench the immune dysregulation.
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[4] Reference: –Trends Immunol. 2021 Jan;42(1):31-44. doi: 10.1016/j.it.2020.11.003
The Commonly used Newer treatment modalities like Immunomodulatory drugs which are currently approved or in trial for COVID-19 are listed below-
- Non-specific Immune modulators
- Corticosteroids such as dexamethasone, methylprednisolone
- Thymosin-alpha
- Macrolides (e.g., azithromycin, clarithromycin),
- Hydroxychloroquine and chloroquine,
- Colchicine,
- Prostaglandin D2 modulators such as ramatroban.
- Heparin: Unfractionated heparin (UFH) and low-molecular weight heparin (LMWH)
- Vitamin C
- Human immunoglobulin
- Specific Immunomodulators
- Serine Protease Inhibitor-Ulinastatin
- Anti-cytokines-Monoclonal Antibodies
- Interleukin (IL)-1 Antagonist(E.g., anakinra)
- IL-6 receptor antagonists (E.g. tocilizumab, sarilumab, siltuximab),
- Anti-CD26 Biologic –Itolizumab
- Janus kinase (JAK) inhibitors (e.g.,baricitinib, ruxolitinib),
- Anti-tumor necrosis factor-α (e.g., adalimumab, infliximab),
- Granulocyte–macrophage colony- stimulating factors (e.g.,gimsilumab, lenzilumab, namilumab),
- VEGF Inhibitor-Bevacizumab
- Convalescent plasma
[5] Reference: The pathogenesis and treatment of the `Cytokine Storm’ in COVID-19
While working as a team for Covid Care I had seen improvement in patients’ condition after use of steroids like dexamethasone or methylprednisolone, vitamin C, vitamin D3 along with antiviral or antibiotics. Some patients have also benefited with the use of Heparin. Newer treatment modalities have been in trial, like other immunomodulators can also control morbidity and mortality.There is repurposed use of certain drugs like Ulinastatin, Thymosin alpha and Mycobacterium W in the management of hospitalized covid19 patients. These drugs are studied and approved in managing sepsis in India or some other country. When used in right dose and at right time they have shown benefit in controlling cytokine storm which is cardinal in moderate to severe covid19. As severe Covid19 nothing but viral sepsis, there use in Covid19 as adjunctive therapy seems logical.[6]. Monoclonal Antibodies (e.g., tocilizumab, baricitinib, bevacizumab) which are artificially lab produced antibodies may neutralize a virus. In USA they have received Emergency use approval by FDA to be used along with steroids or antivirals for management of moderate to severe covid. Hence, theyprevent proinflammatory cytokine storm by increasing regulatory T cells. Plasma therapy plays a role by using the antibodies found in the blood of people who have recovered from an infection (or convalesced), to treat the patients who are infected. Plasma therapy is not actually a vaccine, but instead it gives the infected person’s body a boost to start producing its own antibodies. As the literature suggests, it can also be used in patients whose immune system is too weak to fight the infection. In August 2020US FDA has recentlyapproved use of Convalescent Plasma from patients who have recovered from COVID 19 for the treatment of severe or life threatening COVID-19 infections. The Indian Council of Medical Research (ICMR) initiated PLACID Trial study to assess the safety and efficacy of convalescent plasma to limit COVID-19-associated complications.
The Regulatory agencies for drugs like US FDA (United States Food and Drug Administration), EMA (European Medicines Agency), CDSCO (Central Drugs Standard Control Organization, India) need authentic data and analysis for evaluating safety and efficacy of pharmaceutical drugs. Artificial Intelligence (AI) can be used to provide the information to help regulators for decision. Let us see how?
AI can contribute by use of real-word data like use of electronic health records to know about the efficacy of drug, help in drug discovery and development. The real-world data is more representative about the treatment group than randomized control trial (RCT). But as every coin has two sides using real-world data can be difficult because of, many confounding factors, larger population group, less reliability of data compared to randomized controlled trials.
The scientists across the Globe are working for future potential of Artificial Intelligence by building international or national repositories of electronic health record (EHR) for the help of COVID-19 Researchers. Example of such repository is International Consortium 4CE- which includes the EHRs of patients from 96 hospitals across five countries. The EHRs are matched to a common data model with Integrating Biology and the Bedside60 or Observational Medical Outcomes Partnership (OMOP). Example of repository was used to conduct RCTfrom a COVID-19 registry of nearly 20 000 patients with 1600 COVID-19-positive patients from the Cleveland Clinic Health System EHRs.AI-based identification is currently inthe developmental stage, examples also have shown encouraging results especially for Immunomodulatory drugs in COVID-19, including baricitinib identified by BenevolentAI, dexamethasone predicted by CoV-KGE. Benevolent AI is application of artificial intelligence and machine learning, can be used to modify the way medicines are developed or discovered currently. The hypothesis as predicted by BenevolentAI was similar to the result obtained in clinical trials. Amazon AWS was used recently to identify 41 repurposed drugs including dexamethasone for COVID-19 by utilizing prediction ofCov-KGE.
Genotype-informed treatment (termed personalized drug for COVID-19 treatment) might further improve the success rate of clinical trials. Advances currently made in pharmacogenetics and pharmacogenomics indicate that disease treatment could be considerably improved if therapies were guided by an individual’s genomic profiles. The SARS-CoV-2 infection has shown large inter-individual variabilities, which range from asymptomatic stage to severe and lethal disease. Scientists state the possible hypotheses that human genetics might determine clinical characteristics and drug responses. An example which explains the hypothesis is – analysis of around 81 000 genomes and exomes from the general population predicted that hydroxychloroquine or chloroquine might only work for TMPRSS2-absent patients who are infected by SARS-CoV-2 [14].
These findings feature the importance of pharmacogenomic studies in improving clinical benefits and the success rate of drug repurposing. An Initiative about COVID-19 host genetics is currently underway to generate, analyze and share data in a search for the genetic determinants of COVID-19 susceptibility, severity, outcomes, and personalized treatment. Therefore, AI techniques could provide massive genomic and genetic data to identify the human genetic determinants of SARS-CoV-2 pathogenesis, which presents as a unique opportunity to identify the role of Immunomodulatory drugs targeted for specific patients in COVID-19 [7] (figure 3).
[7] Reference: Lancet Digit Health. 2020 Dec; 2(12): e667–e676.
Up till now, AI’s potential ability to identify new candidate therapies can be made available for clinical trials rapidly and, also if approved, then merging it into health care is unparalleled, also making AI a center piece of advanced technologies. Therefore, AI can be a promising method for identifying role of Newer treatment modalities like Immunomodulatory drugs targeted for specific patient in COVID-19. Availability of big data, including the clinical,biological, and open data (scientific publications and data repositories), novel AI techniques are capable of leveraging these large sets of biomedical data are in high demand. Pharmaceutical scientists, biostatisticians,computer scientists, and physicians are more frequently involved in developing and adopting AI-based technologies for the rapid development of treatment especially for COVID-19. Nevertheless, challenges remain in developing these AI tools, including the security,low quality,data heterogeneity or interpretability of the models[7].
Thus, the future of role of Newer drug modalities like Immunomodulatory drugs is immense in COVID-19, if Artificial Intelligence is used in more collaborative way by Scientists, Pharmaceutical companies and Regulatory organizations the day would not be far when we have conquered the COVID-19 disease.
References-
1. https://www.who.int/emergencies/diseases/novel-coronavirus-2019 [Accessed on 23rd April,2021]
2. https://www.mohfw.gov.in/ [Accessed on 23rd April,2021]
3. Countermeasures to Coronavirus Disease 2019: Are Immunomodulators Rational Treatment Options—A Critical Review of the Evidence Daniel B Chastain, Tia M Stitt, Phong T Ly, Andrés F Henao-Martínez, Carlos Franco-Paredes, Sharmon P Osae Open Forum Infect Dis (2020, Jul). doi: 10.1093/ofid/ofaa219 PMCID: PMC7313774
4. Trends Immunol. 2021 Jan;42(1):31-44. doi: 10.1016/j.it.2020.11.003
5. Ye Q, Wang B, Mao J. The pathogenesis and treatment of the `Cytokine Storm’ in COVID-19. J Infect. 2020 Jun;80(6):607-613 Epub 2020 Apr 10. doi: 10.1016/j.jinf.2020.03.037 PMCID: PMC7194613.
6. Chatterjee, R., Purayil, S. M. P., Ramakrishnan, R. K, Sankaran, R, & Sasikumar, C. S (2020). Efficacy of anti-inflammatory drug ulinastatin in coronavirus disease 2019: A case report. Indian Journal of Case Reports, 6(10), 601-603.Retrieved from https://mansapublishers.com/IJCR/article/view/2602.
7.Yadi Zhou*, Fei Wang*, Jian Tang*, Ruth Nussinov, Feixiong Cheng. Artificial intelligence in COVID-19 drug repurposing Lancet Digital Health 2020; e667–76 (September 18, 2020) https://doi.org/10.1016/ PMCID: PMC7500917
8. Murphy SN, Weber G, Mendis M. Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2) J Am Med Inform Assoc. 2010;17:124–130.
9. Stang PE, Ryan PB, Racoosin JA. Advancing the science for active surveillance: rationale and design for the Observational Medical Outcomes Partnership. Ann Intern Med. 2010;153:600–606.
10. Zhou Y, Hou Y, Shen J. A network medicine approach to prediction and patient-based validation of disease manifestations and drug repurposing for COVID-19. ChemRxiv. 2020 doi: 10.26434/chemrxiv.12579137. published online July 2.
11. Richardson P, Griffin I, Tucker C. Baricitinib as potential treatment for 2019-nCoV acute respiratory disease. Lancet. 2020;395:e30–e31.
12. Group RC, Horby P, Lim WS. Dexamethasone in hospitalised patients with Covid-19—preliminary report. N Engl J Med. 2020 doi: 10.1056/NEJMoa2021436.
13. Zeng X, Song X, Ma T. Repurpose open data to discover therapeutics for COVID-19 using deep learning. J Proteome Res. 2020 doi: 10.1021/acs.jproteome.0c00316.
14. Hou Y, Zhao J, Martin W. New insights into genetic susceptibility of COVID-19: an ACE2 and TMPRSS2 polymorphism analysis. BMC Med. 2020
About Dr. Paridhi Mathur
Dr. Paridhi Mathur, M.B.B.S, M.B.A (H. A)(TISS) (ASSISTANT MANAGER-MEDICAL AFFAIRS, URIHK PHARMACEUTICAL PVT LTD.S/O UREKA HONG KONG LTD.) (EXPERIENCED DOCTOR IN COVID AND CRITICAL CARE)
The author, Dr. Paridhi Mathur, is an experienced Medical Officer who has worked in Critical Care and COVID Care for Central Government Hospital, Mumbai Recently she has moved to explore the horizons in Pharmaceutical Industry. The author is currently working as Assistant Manager-Medical Affairs in Critical Care and Neurology segment for Urihk Pharmaceutical Pvt ltd (s/o Ureka Hong Kong Ltd).
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