Journal of Vaccines & Vaccination

Advancing TB Vaccines: Science, Technology, and Collaboration

Catherine Edith^* Department of Clinical Microbiology, National Institute of Respiratory Diseases (INER), Mexico City, Mexico
^*Correspondence: Catherine Edith, Department of Clinical Microbiology, National Institute of Respiratory Diseases (INER), Mexico City, Mexico, Email:

Received: 03-Jun-2024, Manuscript No. JVV-24-26114; Editor assigned: 05-Jun-2024, Pre QC No. JVV-24-26114 (PQ); Reviewed: 19-Jun-2024, QC No. JVV-24-26114; Revised: 26-Jun-2024, Manuscript No. JVV-24-26114 (R); Published: 03-Jul-2024, DOI: 10.35248/2157-7560.24.S27.001

About the Study

Tuberculosis (TB) remains one of the most challenging infectious diseases, causing immense morbidity and mortality globally. Despite significant advances in medical science, the development of effective vaccines against TB has been slow. The Bacillus Calmette-Guerin (BCG) vaccine, developed nearly a century ago, provides limited protection against pulmonary TB in adults, which underscores the urgent need for new and more effective vaccines [1]. Accelerating Research and Development (R&D) in this field is important for controlling and eventually eliminating TB.

The pathogen responsible for TB, Mycobacterium tuberculosis, has a complex interaction with the human immune system, which complicates vaccine development. Mycobacterium tuberculosis can evade immune responses and establish latent infections, which may reactivate years later. This ability to persist and reactivate makes it a formidable target for vaccine development [2]. A successful TB vaccine must not only prevent initial infection but also eliminate latent bacteria and prevent reactivation.

Several strategies are being explored to accelerate TB vaccine development. One approach is the enhancement of preclinical models that better mimic human TB. Traditional models, such as mice, have limitations in replicating human disease pathology and immune responses [3]. Therefore, researchers are turning to more sophisticated models, such as non-human primates and genetically modified mice that better reflect human immune responses to Mycobacterium tuberculosis. These models can provide more accurate data on vaccine efficacy and safety, thereby speeding up the transition from preclinical to clinical stages.

Another key aspect of accelerating TB vaccine R&D is the identification and validation of new antigens. Mycobacterium tuberculosis has a vast array of antigens, but not all are suitable targets for a vaccine [4-6]. Advanced techniques in genomics, proteomics, and bioinformatics are being used to identify antigens that elicit strong and protective immune responses. Once identified, these antigens can be engineered into various vaccine platforms, including viral vectors, recombinant proteins, and DNA vaccines.

The use of adjuvants is another critical factor in vaccine development. Adjuvants enhance the immune response to the vaccine antigen, increasing its efficacy. Novel adjuvants that can stimulate the appropriate type of immune response, particularly a strong T-cell response, are being investigated [7]. This is important because a strong cellular immune response is necessary to control and eliminate Mycobacterium tuberculosis.

Moreover, clinical trials for TB vaccines are evolving to become more efficient. Adaptive trial designs, which allow for modifications based on interim results, can accelerate the evaluation of vaccine candidates. This approach reduces the time and resources needed to identify potential vaccines. Additionally, according to regulatory requirements across different countries can streamline the approval process for conducting international clinical trials, which is essential given the global nature of TB.

Collaboration and funding are also pivotal in accelerating TB vaccine R&D. Public-private partnerships, international collaborations, and increased funding from governments and philanthropic organizations can provide the necessary resources and infrastructure. Initiatives like the TB Vaccine Initiative (TBVI) and the Aeras Global TB Vaccine Foundation have been instrumental in driving research efforts and fostering collaborations across different sectors [8].

The integration of innovative technologies is another aspiring avenue. Advances in systems biology and Artificial Intelligence (AI) can significantly impact TB vaccine development. Systems biology approaches can provide comprehensive insights into the immune response to TB and identify novel biomarkers for vaccine efficacy. AI and machine learning can analyze vast amounts of data from clinical trials, predict vaccine outcomes, and optimize vaccine formulations.

Importantly, the lessons learned from the COVID-19 pandemic can be applied to TB vaccine development. The rapid development and deployment of COVID-19 vaccines demonstrated the potential of mRNA technology and the benefits of global collaboration. mRNA vaccines can be rapidly designed and manufactured, offering an encouraging platform for TB vaccines [9]. Additionally, the global infrastructure established for COVID-19 vaccine distribution can be used for TB vaccines.

However, the accelerated development of TB vaccines must be balanced with rigorous safety and efficacy evaluations. While speed is important, ensuring that new vaccines are safe and effective is very important [10]. This requires challenging clinical trials and long-term follow-up studies to monitor for potential adverse effects and sustained immunity.

Conclusion

In conclusion, accelerating the research and development of new vaccines against tuberculosis is a multifaceted challenge that requires advancements in scientific research, innovative technologies, efficient clinical trial designs, and strong global collaboration. By using modern scientific tools and fostering international partnerships, we can make significant strides towards developing effective TB vaccines. This will not only save lives but also contribute to the global effort to eradicate TB.

References

1. XOFLUZA (baloxavir marboxil)-Prescribing information. Genentech USA Inc. 2018.
2. Dobson J, Whitley RJ, Pocock S, Monto AS. Oseltamivir treatment for influenza in adults: a meta-analysis of randomised controlled trials. The Lancet. 2015;385(9979):1729-1737.

   [Crossref] [Google Scholar] [PubMed]

3. Venkatesan S, Myles PR, Leonardi-Bee J, Muthuri SG, Al Masri M, Andrews N. Impact of outpatient neuraminidase inhibitor treatment in patients infected with Influenza A (H1N1) pdm09 at high risk of hospitalization: An individual participant data metaanalysis. Clin Infect Dis. 2017;64(10):1328-1334.

   [Crossref] [Google Scholar] [PubMed]

4. Hayden FG, Sugaya N, Hirotsu N, Lee N, Hurt AC, Watanabe A. Baloxavir marboxil for uncomplicated influenza in adults and adolescents. N Engl J Med. 2018;379(10):913-924.

   [Crossref], [Google Scholar] [PubMed]

5. Heneghan CJ, Onakpoya I, Jones MA, Doshi P, Hama R, Jefferson T. Neuraminidase inhibitors for influenza: a systematic review and meta-analysis of regulatory and mortality data. Health Technol Assess. 2016;20(42):1-242.

   [Crossref] [Google Scholar] [PubMed]

6. Doll MK, Winters N, Boikos C, Kraicer-Melamed H, Gore G, Quach C. Safety and effectiveness of neuraminidase inhibitors for influenza treatment, prophylaxis, and outbreak control: a systematic review of systematic reviews and/or meta-analyses. J Antimicrob Chemother. 2017;72(11):2990-3007.

   [Crossref] [Google Scholar] [PubMed]

7. Stewart RJ, Flannery B, Chung JR, Gaglani M, Reis M, Zimmerman RK. Influenza antiviral prescribing for outpatients with an acute respiratory illness and at high risk for influenza-associated complications during 5 influenza seasons-United States, 2011-2016. Clin Infect Dis. 2018;66(7):1035-1041.

   [Crossref] [Google Scholar] [PubMed]

8. Spagnuolo PJ, Zhang M, Xu Y, Han J, Liu S, Liu J. Effects of antiviral treatment on influenza-related complications over four influenza seasons: 2006-2010. Curr Med Res Opin. 2016;32(8):1399-1407.

   [Crossref] [Google Scholar] [PubMed]

9. Wallick C, Wu N, To TM, Keebler D, Moawad D. Antiviral use is associated with a decrease in the rate of influenza-related complications, health care resource utilization, and costs. J Med Econ. 2021;24(1):386-393.

   [Crossref] [Google Scholar] [PubMed]

10. Neuberger EE, To TM, Seetasith A, Arndorfer SM, Wallick CJ. Antiviral use and health care use among patients with rheumatoid arthritis and influenza in three influenza seasons, 2016‐2019. ACR Open Rheumatology. 2022;4(7):631-639.

    [Crossref] [Google Scholar] [PubMed]