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Abstract

Small molecule inhibitors have emerged as pivotal therapeutic agents in targeting cancer, inflammation, and autoimmune diseases. These compounds are designed to interfere with specific molecular pathways, offering improved efficacy and reduced side effects. This review explores the latest advances in small molecule inhibitors, highlighting key mechanisms, recent clinical developments, and future directions in their application for disease treatment.

Keywords

Small Molecule Inhibitors, Cancer Therapy, Inflammation, Autoimmune Diseases, Targeted Therapy, Kinase Inhibitors

Introduction

Cancer, inflammatory disorders, and autoimmune diseases pose significant global health burdens, affecting millions of people worldwide. Despite advances in medical research, the limitations of traditional therapies—such as chemotherapy, corticosteroids, and biologics—have prompted the development of more precise and effective treatment strategies. Conventional treatments often exhibit poor specificity, leading to systemic toxicity, severe side effects, and, in many cases, the development of drug resistance. As a result, there is an urgent need for novel therapeutic approaches that can selectively target disease-causing molecular pathways while minimizing adverse effects.

The Role of Small Molecule Inhibitors

Small molecule inhibitors (SMIs) have emerged as a transformative class of drugs that selectively interfere with critical signaling pathways implicated in disease progression. These low-molecular-weight compounds (<900 Da) exhibit high cell permeability, allowing them to reach intracellular targets that were previously considered undruggable by larger biomolecules such as monoclonal antibodies. Unlike traditional chemotherapeutic agents, which non-selectively target rapidly dividing cells, SMIs provide a more tailored approach by modulating specific molecular interactions within cancer cells, immune pathways, or inflammatory cascades.

Advantages of Small Molecule Inhibitors

The success of SMIs can be attributed to several key advantages over conventional therapies:

  1. High Specificity – SMIs are designed to bind with precise molecular targets, such as kinases, proteases, and transcription factors, reducing off-target toxicity.
  2. Oral Bioavailability – Many SMIs can be administered orally, improving patient compliance compared to injectable biologics.
  3. Tissue and Cellular Penetration – Due to their small size, these molecules can efficiently penetrate tissues and cross cell membranes, enabling them to modulate intracellular signaling pathways.
  4. Reversible and Tunable Binding – Unlike biologics, which often lead to irreversible inhibition, SMIs can be designed to exhibit reversible binding, allowing for better control over drug activity and fewer long-term complications.
  5. Cost-Effectiveness – Small molecules are generally easier and less expensive to synthesize compared to complex biologics, making them more accessible in clinical practice.

Applications in Disease Treatment

SMIs have been successfully applied across multiple therapeutic areas:

  • Oncology: Many cancers are driven by dysregulated kinases that promote uncontrolled cell proliferation and survival. Kinase inhibitors such as imatinib (targeting BCR-ABL in chronic myeloid leukemia) and erlotinib (targeting EGFR in lung cancer) have revolutionized cancer therapy by selectively blocking oncogenic signaling.
  • Inflammatory Disorders: Pro-inflammatory cytokines and signaling molecules play a crucial role in diseases such as rheumatoid arthritis and inflammatory bowel disease. Janus kinase (JAK) inhibitors, including tofacitinib, have demonstrated efficacy in modulating immune responses.
  • Autoimmune Diseases: In conditions like lupus and multiple sclerosis, small molecules targeting immune checkpoints and intracellular signaling cascades have shown promise in reducing disease activity while minimizing the risks associated with broad immunosuppression.

Challenges and Future Directions

Despite their advantages, SMIs also face challenges that limit their widespread use. These include:

  • Drug Resistance: Many cancers develop resistance to kinase inhibitors through secondary mutations or alternative pathway activation. Combination therapies and next-generation inhibitors aim to overcome this issue.
  • Toxicity and Side Effects: Off-target interactions and long-term toxicity remain concerns, necessitating further refinement in drug design.
  • Pharmacokinetic Limitations: Some SMIs suffer from poor solubility, rapid metabolism, or insufficient half-life, requiring novel formulation strategies.
  • Targeting Protein-Protein Interactions: While kinases and enzymes are common SMI targets, modulating protein-protein interactions remains a challenge due to the complexity of their binding sites.

2. Mechanisms of Action of Small Molecule Inhibitors

Small molecule inhibitors (SMIs) exert their therapeutic effects by selectively targeting key molecular pathways involved in disease progression. These compounds interfere with cellular processes such as signal transduction, immune regulation, inflammation, and gene expression. Understanding the diverse mechanisms by which SMIs function is crucial for optimizing their clinical application and overcoming resistance.

2.1 Kinase Inhibition

Protein kinases play a fundamental role in cellular signaling by phosphorylating target proteins, regulating cell proliferation, differentiation, apoptosis, and immune responses. Aberrant kinase activity is frequently observed in cancer and inflammatory diseases, making kinases attractive drug targets.

2.1.1 Tyrosine Kinase Inhibitors (TKIs)

Tyrosine kinases are enzymes that transfer phosphate groups to tyrosine residues on proteins, modulating key signaling cascades such as the epidermal growth factor receptor (EGFR), vascular endothelial growth factor receptor (VEGFR), and BCR-ABL pathways.

  • Imatinib (Gleevec) – A selective BCR-ABL tyrosine kinase inhibitor used in chronic myeloid leukemia (CML). It prevents ATP binding to the kinase domain, blocking downstream signaling and inhibiting cancer cell proliferation.
  • Gefitinib and Erlotinib – EGFR inhibitors used in non-small cell lung cancer (NSCLC) that disrupt EGFR-mediated signaling, leading to reduced tumor growth.
  • Sunitinib – A multi-kinase inhibitor targeting VEGFR, PDGFR, and KIT, used in renal cell carcinoma and gastrointestinal stromal tumors.

2.1.2 Serine/Threonine Kinase Inhibitors

These inhibitors target kinases that regulate phosphorylation of serine/threonine residues, which play critical roles in cell cycle progression and immune regulation.

  • Vemurafenib – Targets mutant BRAF V600E kinase in melanoma, blocking the MAPK/ERK signaling pathway.
  • Palbociclib – A CDK4/6 inhibitor used in breast cancer that disrupts cell cycle progression by inhibiting cyclin-dependent kinases.

Kinase inhibitors have transformed cancer treatment by offering targeted therapy with reduced systemic toxicity compared to conventional chemotherapy. However, resistance mechanisms, such as secondary mutations and alternative pathway activation, remain a challenge.

2.2 Immune Checkpoint Modulation

The immune system is tightly regulated by checkpoint molecules that prevent excessive immune activation and autoimmunity. Cancer cells exploit these checkpoints to evade immune detection, leading to unchecked tumor growth.

  • Small molecule inhibitors targeting immune checkpoints restore immune system activity against cancer cells by blocking inhibitory pathways.
  • PD-1/PD-L1 Inhibitors – Programmed death-1 (PD-1) and its ligand PD-L1 suppress T-cell activation, allowing cancer cells to escape immune surveillance. Small molecules targeting this pathway (in addition to monoclonal antibodies) are being explored to improve immune responses in cancer.
  • CTLA-4 Inhibitors – Cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) inhibits early-stage T-cell activation. Targeting this pathway enhances T-cell proliferation and immune attack against tumors.
  • While monoclonal antibodies like pembrolizumab (Keytruda) and nivolumab have been the dominant checkpoint inhibitors, research into small-molecule alternatives is ongoing, with the goal of improving oral bioavailability and reducing immune-related adverse events.

2.3 Cytokine and Inflammatory Mediator Suppression

Cytokines are signaling proteins that regulate immune responses and inflammation. Dysregulated cytokine production is implicated in autoimmune diseases, chronic inflammatory conditions, and cancer progression. Small molecule inhibitors can modulate these pathways by directly blocking cytokine production or interfering with downstream signaling.

2.3.1 Janus Kinase (JAK) Inhibitors

The JAK-STAT pathway plays a pivotal role in cytokine signaling and immune regulation. Abnormal activation contributes to autoimmune diseases such as rheumatoid arthritis and inflammatory bowel disease.

  • Tofacitinib – A JAK1/3 inhibitor that blocks IL-2, IL-6, and interferon signaling, reducing inflammation in rheumatoid arthritis and ulcerative colitis.
  • Ruxolitinib – A JAK1/2 inhibitor used in myelofibrosis and polycythemia vera to suppress excessive inflammatory signaling.

2.3.2 Tumor Necrosis Factor-alpha (TNF-α) Inhibitors

TNF-α is a key pro-inflammatory cytokine involved in autoimmune diseases. While biologics like infliximab target TNF-α extracellularly, small molecules that inhibit TNF-α synthesis or signaling are being developed to provide oral alternatives.

2.3.3 IL-6 and IL-17 Inhibitors

IL-6 and IL-17 are critical mediators in autoimmune diseases such as psoriasis and multiple sclerosis. Small molecule inhibitors targeting these pathways aim to reduce inflammation with fewer side effects than biologic therapies.

2.4 Epigenetic Modulation

Epigenetic changes, including DNA methylation and histone modification, play a crucial role in gene expression and disease progression. Small molecule inhibitors targeting epigenetic regulators can alter gene transcription patterns, providing therapeutic benefits in cancer and inflammatory diseases.

2.4.1 Histone Deacetylase (HDAC) Inhibitors

HDACs remove acetyl groups from histones, leading to chromatin condensation and gene repression. Inhibiting HDACs restores normal gene expression patterns, promoting tumor suppression and immune regulation.

  • Vorinostat (SAHA) – An HDAC inhibitor used in cutaneous T-cell lymphoma that reactivates tumor suppressor genes.
  • Panobinostat – Targets multiple HDAC isoforms, showing efficacy in multiple myeloma.

2.4.2 DNA Methyltransferase (DNMT) Inhibitors

DNMTs add methyl groups to DNA, leading to gene silencing. In cancer, hypermethylation often inactivates tumor suppressor genes.

  • Azacitidine and Decitabine – DNMT inhibitors that reactivate silenced genes, restoring normal cell function in leukemia and myelodysplastic syndromes.
  • Epigenetic therapies hold promise for reprogramming aberrant gene expression in cancer, but challenges such as specificity and off-target effects remain.

3. Comparative Analysis of Clinical Efficacy

Inhibitor Class

Example Drugs

Cancer Type

Clinical Outcome

TKIs

Imatinib

CML

High remission rates, but resistance observed

TKIs

Gefitinib, Erlotinib

NSCLC

Improved survival in EGFR-mutant patients

BRAF Inhibitors

Vemurafenib

Melanoma

Effective in BRAF V600E tumors, but resistance develops

PARP Inhibitors

Olaparib

Ovarian/Breast Cancer

Effective in BRCA-mutated tumors

HDAC Inhibitors

Vorinostat

T-cell Lymphomas

Modest efficacy, used in combination therapy

4. Resistance Mechanisms and Challenges

Despite their success, small molecule inhibitors face challenges due to resistance mechanisms:

  • Secondary Mutations: Mutations in kinase domains (e.g., T315I mutation in BCR-ABL) reduce drug binding.
  • Alternative Pathway Activation: Tumors bypass inhibition by activating compensatory signaling pathways.
  • Epigenetic Adaptation: Cancer cells modify gene expression to evade targeted therapy.

Future Directions

As research in targeted therapies continues to evolve, several promising strategies are emerging to enhance treatment efficacy and overcome resistance mechanisms.

  • Combination Therapies: One of the most effective approaches involves combining multiple inhibitors or integrating targeted therapies with immunotherapy. By using a combination of drugs that act on different pathways, researchers aim to reduce the likelihood of resistance while enhancing therapeutic outcomes. Immunotherapy, which harnesses the body's immune system to fight disease, can be particularly effective when used alongside targeted inhibitors, potentially leading to more durable responses in patients.
  • Next-Generation Inhibitors: The development of allosteric inhibitors represents a significant advancement in targeted therapy. Unlike traditional inhibitors that bind directly to the active site of an enzyme or receptor, allosteric inhibitors target non-traditional binding sites, leading to more selective and potentially less toxic effects. These next-generation inhibitors can help circumvent common resistance mechanisms that arise due to mutations in the active site, thereby extending the effectiveness of treatment options.
  • Personalized Medicine: With advancements in genetic and molecular profiling, personalized medicine is becoming a cornerstone of modern treatment strategies. By analyzing a patient's genetic makeup, researchers and clinicians can tailor treatments to match individual characteristics, improving response rates and minimizing adverse effects. This approach ensures that therapies are more precisely targeted, leading to better patient outcomes and reduced instances of trial-and-error prescribing.

RESULTS AND CONCLUSIONS

  • The advancement of targeted therapies has significantly improved treatment outcomes, particularly in diseases with well-defined molecular drivers. However, challenges such as drug resistance and limited response in certain patient populations highlight the need for continued innovation.

Results:

  • Combination therapies have shown promise in overcoming resistance mechanisms by targeting multiple pathways simultaneously. Early clinical trials indicate that integrating inhibitors with immunotherapy can enhance treatment efficacy and prolong responses.
  • Next-generation inhibitors, particularly allosteric inhibitors, offer a novel approach by targeting non-traditional binding sites, potentially reducing toxicity and overcoming resistance caused by mutations in the active site.
  • Personalized medicine, driven by genetic profiling, has improved treatment precision, leading to better response rates and fewer side effects compared to traditional one-size-fits-all approaches.

Conclusions:
The future of targeted therapy lies in a multifaceted approach that incorporates combination strategies, next-generation drug development, and personalized treatment plans. While significant progress has been made, continued research and clinical trials are necessary to refine these strategies and expand their applicability across a broader range of diseases. By integrating these advancements, the field is moving closer to achieving more effective and durable treatment options, ultimately improving patient outcomes.

REFERENCES

  1. Sharma, P., & Allison, J. P. (2015). The future of immune checkpoint therapy. Science, 348(6230), 56-61.
  2. Hanahan, D., & Weinberg, R. A. (2011). Hallmarks of cancer: the next generation. Cell, 144(5), 646-674.
  3. Al-Lazikani, B., Banerji, U., & Workman, P. (2012). Combinatorial drug therapy for cancer in the post-genomic era. Nature Biotechnology, 30(7), 679-692.
  4. Yap, T. A., Aerts, H. J., Popat, S., & de Bono, J. S. (2013). Novel insights into drug resistance mechanisms and implications for clinical practice. Clinical Cancer Research, 19(7), 1467-1477.
  5. Engelman, J. A., Zejnullahu, K., & Mitsudomi, T. (2007). MET amplification leads to gefitinib resistance in lung cancer by activating ERBB3 signaling. Science, 316(5827), 1039-1043.
  6. Garraway, L. A., & Jaenne, P. A. (2012). Circumventing cancer drug resistance in the era of personalized medicine. Cancer Discovery, 2(3), 214-226.
  7. Baselga, J. (2011). Targeting the phosphoinositide-3 (PI3) kinase pathway in breast cancer. The Oncologist, 16(Suppl 1), 12-19.
  8. Holohan, C., Van Schaeybroeck, S., Longley, D. B., & Johnston, P. G. (2013). Cancer drug resistance: an evolving paradigm. Nature Reviews Cancer, 13(10), 714-726.
  9. Chen, D. S., & Mellman, I. (2013). Oncology meets immunology: the cancer-immunity cycle. Immunity, 39(1), 1-10.
  10. Flaherty, K. T., Infante, J. R., Daud, A., Gonzalez, R., Kefford, R. F., Sosman, J., ... & Kim, K. B. (2012). Combined BRAF and MEK inhibition in melanoma. New England Journal of Medicine, 367(18), 1694-1703.
  11. Swanton, C. (2012). Intratumor heterogeneity: evolution through space and time. Cancer Research, 72(19), 4875-4882.
  12. Wang, Q., & Yu, L. (2019). Advances in allosteric inhibitors of kinases: targeting beyond the active site. Chemical Society Reviews, 48(7), 1873-1903.
  13. Komander, D., & Rape, M. (2012). The ubiquitin code. Annual Review of Biochemistry, 81, 203-229.
  14. Hyman, D. M., Puzanov, I., & Subbiah, V. (2017). Precision medicine in cancer therapy. Nature Reviews Clinical Oncology, 14(7), 397-411.
  15. Dienstmann, R., Jang, I. S., Bot, B., Friend, S., & Guinney, J. (2015). Database of genomic biomarkers for cancer drugs and clinical targetability in solid tumors. Cancer Discovery, 5(2), 118-123.
  16. Sawyers, C. (2004). Targeted cancer therapy. Nature, 432(7015), 294-297.
  17. Brose, M. S., Volpe, P., Feldman, M., Kumar, M., Rishi, I., Gerrero, R., ... & Baffa, R. (2002). BRAF and RAS mutations in human lung cancer and melanoma. Cancer Research, 62(23), 6997-7000.
  18. Planchard, D., Smit, E. F., Groen, H. J., Mazieres, J., Besse, B., Helland, Å., ... & Blackhall, F. (2018). Dabrafenib plus trametinib in patients with previously treated BRAF V600E–mutant metastatic non-small-cell lung cancer: an open-label, multicentre phase 2 trial. The Lancet Oncology, 18(10), 1307-1316.
  19. Wilson, T. R., Fridlyand, J., Yan, Y., Penuel, E., Burton, L., Chan, E., ... & Merchant, M. (2012). Widespread potential for growth-factor-driven resistance to anticancer kinase inhibitors. Nature, 487(7408), 505-509.
  20. Heinemann, V., Douillard, J. Y., Ducreux, M., & Peeters, M. (2013). Targeted therapy in metastatic colorectal cancer—an example of personalized medicine in action. Cancer Treatment Reviews, 39(6), 592-601.
  21. Van Allen, E. M., Wagle, N., & Levy, M. A. (2013). Clinical applications of advanced genomics in cancer: precision medicine at the crossroads. Cancer Discovery, 3(7), 649-655.
  22. Murtaza, M., Dawson, S. J., Pogrebniak, K., et al. (2013). Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA. Nature, 497(7447), 108-112.
  23. Hodi, F. S., O’Day, S. J., McDermott, D. F., et al. (2010). Improved survival with ipilimumab in patients with metastatic melanoma. New England Journal of Medicine, 363(8), 711-723.
  24. Robert, C., Thomas, L., Bondarenko, I., et al. (2011). Ipilimumab plus dacarbazine for previously untreated metastatic melanoma. New England Journal of Medicine, 364(26), 2517-2526.
  25. Ribas, A., & Wolchok, J. D. (2018). Cancer immunotherapy using checkpoint blockade. Science, 359(6382), 1350-1355.
  26. Flaherty, K. T., & McArthur, G. A. (2010). BRAF, a target in melanoma: implications for solid tumor drug development. Cancer Cell, 18(5), 510-512.
  27. Baselga, J., & Swain, S. M. (2009). Novel anticancer targets: revisiting ERBB2 and discovering ERBB3. Nature Reviews Cancer, 9(7), 463-475.
  28. Davies, H., Bignell, G. R., Cox, C., et al. (2002). Mutations of the BRAF gene in human cancer. Nature, 417(6892), 949-954.
  29. Schreiber, R. D., Old, L. J., & Smyth, M. J. (2011). Cancer immunoediting: integrating immunity’s roles in cancer suppression and promotion. Science, 331(6024), 1565-1570. 30-40. Additional references can be found in PubMed and Google Scholar under targeted therapy, personalized medicine, and combination therapy in oncology.

Reference

  1. Sharma, P., & Allison, J. P. (2015). The future of immune checkpoint therapy. Science, 348(6230), 56-61.
  2. Hanahan, D., & Weinberg, R. A. (2011). Hallmarks of cancer: the next generation. Cell, 144(5), 646-674.
  3. Al-Lazikani, B., Banerji, U., & Workman, P. (2012). Combinatorial drug therapy for cancer in the post-genomic era. Nature Biotechnology, 30(7), 679-692.
  4. Yap, T. A., Aerts, H. J., Popat, S., & de Bono, J. S. (2013). Novel insights into drug resistance mechanisms and implications for clinical practice. Clinical Cancer Research, 19(7), 1467-1477.
  5. Engelman, J. A., Zejnullahu, K., & Mitsudomi, T. (2007). MET amplification leads to gefitinib resistance in lung cancer by activating ERBB3 signaling. Science, 316(5827), 1039-1043.
  6. Garraway, L. A., & Jaenne, P. A. (2012). Circumventing cancer drug resistance in the era of personalized medicine. Cancer Discovery, 2(3), 214-226.
  7. Baselga, J. (2011). Targeting the phosphoinositide-3 (PI3) kinase pathway in breast cancer. The Oncologist, 16(Suppl 1), 12-19.
  8. Holohan, C., Van Schaeybroeck, S., Longley, D. B., & Johnston, P. G. (2013). Cancer drug resistance: an evolving paradigm. Nature Reviews Cancer, 13(10), 714-726.
  9. Chen, D. S., & Mellman, I. (2013). Oncology meets immunology: the cancer-immunity cycle. Immunity, 39(1), 1-10.
  10. Flaherty, K. T., Infante, J. R., Daud, A., Gonzalez, R., Kefford, R. F., Sosman, J., ... & Kim, K. B. (2012). Combined BRAF and MEK inhibition in melanoma. New England Journal of Medicine, 367(18), 1694-1703.
  11. Swanton, C. (2012). Intratumor heterogeneity: evolution through space and time. Cancer Research, 72(19), 4875-4882.
  12. Wang, Q., & Yu, L. (2019). Advances in allosteric inhibitors of kinases: targeting beyond the active site. Chemical Society Reviews, 48(7), 1873-1903.
  13. Komander, D., & Rape, M. (2012). The ubiquitin code. Annual Review of Biochemistry, 81, 203-229.
  14. Hyman, D. M., Puzanov, I., & Subbiah, V. (2017). Precision medicine in cancer therapy. Nature Reviews Clinical Oncology, 14(7), 397-411.
  15. Dienstmann, R., Jang, I. S., Bot, B., Friend, S., & Guinney, J. (2015). Database of genomic biomarkers for cancer drugs and clinical targetability in solid tumors. Cancer Discovery, 5(2), 118-123.
  16. Sawyers, C. (2004). Targeted cancer therapy. Nature, 432(7015), 294-297.
  17. Brose, M. S., Volpe, P., Feldman, M., Kumar, M., Rishi, I., Gerrero, R., ... & Baffa, R. (2002). BRAF and RAS mutations in human lung cancer and melanoma. Cancer Research, 62(23), 6997-7000.
  18. Planchard, D., Smit, E. F., Groen, H. J., Mazieres, J., Besse, B., Helland, Å., ... & Blackhall, F. (2018). Dabrafenib plus trametinib in patients with previously treated BRAF V600E–mutant metastatic non-small-cell lung cancer: an open-label, multicentre phase 2 trial. The Lancet Oncology, 18(10), 1307-1316.
  19. Wilson, T. R., Fridlyand, J., Yan, Y., Penuel, E., Burton, L., Chan, E., ... & Merchant, M. (2012). Widespread potential for growth-factor-driven resistance to anticancer kinase inhibitors. Nature, 487(7408), 505-509.
  20. Heinemann, V., Douillard, J. Y., Ducreux, M., & Peeters, M. (2013). Targeted therapy in metastatic colorectal cancer—an example of personalized medicine in action. Cancer Treatment Reviews, 39(6), 592-601.
  21. Van Allen, E. M., Wagle, N., & Levy, M. A. (2013). Clinical applications of advanced genomics in cancer: precision medicine at the crossroads. Cancer Discovery, 3(7), 649-655.
  22. Murtaza, M., Dawson, S. J., Pogrebniak, K., et al. (2013). Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA. Nature, 497(7447), 108-112.
  23. Hodi, F. S., O’Day, S. J., McDermott, D. F., et al. (2010). Improved survival with ipilimumab in patients with metastatic melanoma. New England Journal of Medicine, 363(8), 711-723.
  24. Robert, C., Thomas, L., Bondarenko, I., et al. (2011). Ipilimumab plus dacarbazine for previously untreated metastatic melanoma. New England Journal of Medicine, 364(26), 2517-2526.
  25. Ribas, A., & Wolchok, J. D. (2018). Cancer immunotherapy using checkpoint blockade. Science, 359(6382), 1350-1355.
  26. Flaherty, K. T., & McArthur, G. A. (2010). BRAF, a target in melanoma: implications for solid tumor drug development. Cancer Cell, 18(5), 510-512.
  27. Baselga, J., & Swain, S. M. (2009). Novel anticancer targets: revisiting ERBB2 and discovering ERBB3. Nature Reviews Cancer, 9(7), 463-475.
  28. Davies, H., Bignell, G. R., Cox, C., et al. (2002). Mutations of the BRAF gene in human cancer. Nature, 417(6892), 949-954.
  29. Schreiber, R. D., Old, L. J., & Smyth, M. J. (2011). Cancer immunoediting: integrating immunity’s roles in cancer suppression and promotion. Science, 331(6024), 1565-1570. 30-40. Additional references can be found in PubMed and Google Scholar under targeted therapy, personalized medicine, and combination therapy in oncology.

Photo
Aditi Jyotishi
Corresponding author

Dr. Vedprakash Patil Pharmacy College

Photo
Roshani Bhavsar
Co-author

SNBP College of Pharmacy, Chikhali

Photo
Roshani Bhavsar
Co-author

MES’s College of Pharmacy, Sonai

Photo
Ashvini Patmase
Co-author

Laxminarayan College of pharmacy, Khamgaon

Photo
Shubham Ahir
Co-author

NK College of Pharmacy, Khamgaon

Photo
Kamran Ahmad Shaikh Zaheer Ahmed
Co-author

NK College of Pharmacy, Khamgaon

Aditi Jyotishi*, Roshani Bhavsar, Chetan Kedari, Ashvini Patmase, Shubham Ahir, Kamran Ahmad Shaikh Zaheer Ahmed, Advances in Small Molecule Inhibitors for Cancer Inflammation and Autoimmune Diseases, Int. J. of Pharm. Sci., 2025, Vol 3, Issue 4, 508-515. https://doi.org/10.5281/zenodo.15147735

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