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In response to the FDA and EMA's emphasis on understanding the molecular and physiological basis of therapies, Anaxomics proposes TPMS technology, enabling computational simulation of human pathophysiology.

This groundbreaking approach unveils the likely mechanisms underlying drugs' clinical responses, aligning with new regulatory requirements.

What does Anaxomics offer?

Enhancing Understanding of Disease Pathogenesis

Failures in preclinical development can often be attributed to deficiencies in our understanding of disease pathogenesis and the selection of appropriate therapeutic targets. Anaxomics is committed to improving human health by assisting clients in comprehending clinical observations and placing them within the broader context of human physiology. By doing so, we help identify potential pitfalls and refine strategies for more effective disease management.

Achieving a Comprehensive Understanding of Drug Safety and Efficacy

In the early stages of drug discovery, accurate prediction of efficacy and safety is crucial. Anaxomics' TPMS technology offers the ability to compare and select the most promising candidates while considering other therapeutic options. This ensures a comprehensive evaluation of the safety and efficacy profile during the drug discovery and development process.


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ADR: adverse drug reaction

Gaining Insights into Drugs' Clinical Responses

Whether in clinical trial phases or once a drug has entered the market, understanding the mechanisms of action is of utmost importance. Anaxomics' TPMS technology facilitates the exploration of unexpected drug-induced adverse drug reactions (ADRs) observed during trials ( Wagg, 2017 ; Jorba, 2020; Córdoba, 2022). Additionally, it helps unravel the efficacy of drugs or drug combinations observed in phase II, phase III, real-world evidence (RWE), or clinical practice settings (Durán, 2022; Segú-Vergés, 2023; Bayes-Genis, 2021; Iborra-Egea, 2017; Lozano, 2021; Segú-Vergés, 2021; Díaz-Beyá, 2022; Carcereny, 2021). Furthermore, it contributes to advancing personalized medicine by enhancing our understanding of drug efficacy and safety (Segú-Vergés, 2023).

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Durán, I., D. Castellano, J. Puente, L. Martín-Couce, E. Bello, U. Anido, J. M. Mas and L. Costa (2022). Exploring the synergistic effects of cabozantinib and a programmed cell death protein 1 inhibitor in metastatic renal cell carcinoma with machine learning. Oncotarget 13: p. 237-256.

The image on the left shows the molecular pathways associated with a specific mechanism of action (MoA) identified through TPMS technology. On the right, the illustration is a representation of a total of five identified MoAs, integrated into a single figure providing context and visualizing the interconnectedness of the identified mechanisms. Both images correspond to the same project carried out for IPSEN (Durán, 2022).

Publications

  • Wagg, J., O. Krieter, C. Ooi, S. Croset, M. Leddin, R. Valls, J. M. Mas and C. Boetsch (2017). Effect of molecular mechanisms mediating bevacizumab (BEV) and vanucizumab (VAN) on gastrointestinal perforation: Use of artificial neural networks for integrated data analysis. ASCO Annual Meeting: American Society of Clinical Oncology.
    DOI: 10.1200/JCO.2017.35.15_suppl.e15108

  • Jorba G., J. Aguirre-Plans, V. Junet, C. Segú-Vergés, J. L. Ruiz, A. Pujol, N. Fernández-Fuentes, J. M. Mas, B. Oliva (2020). In-silico simulated prototype-patients using TPMS technology to study a potential adverse effect of sacubitril and valsartan. PLoS One. Feb 13;15(2):e0228926.
    DOI: 10.1371/journal.pone.0228926

  • Córdoba, R., D. Colomer, A. Bayés-Genís, C. Leiva Farre, E. Álvarez, M.D. López and E. Zatarain (2022). In silico Evaluation of BTK Inhibitors Mechanisms That Could Induce Atrial Fibrillation and Hypertension in the Treatment of Chronic Lymphocytic Leukemia. Presented at 64th ASH Annual Meeting & Exposition.
    DOI: 10.1182/blood-2022-158963

  • Durán, I., D. Castellano, J. Puente, L. Martín-Couce, E. Bello, U. Anido, J. M. Mas and L. Costa (2022). Exploring the synergistic effects of cabozantinib and a programmed cell death protein 1 inhibitor in metastatic renal cell carcinoma with machine learning. Oncotarget 13: p. 237-256.
    DOI: 10.18632/oncotarget.28183

  • Segú-Vergés, C., L. Artigas, M. Coma and R. W. Peck (2023). Artificial Intelligence Assessment of the Potential of Tocilizumab Along with Corticosteroids Therapy for the Management of Covid-19 Evoked Acute Respiratory Distress Syndrome. PLoS One. 18, no. 2: e0280677.
    DOI: 10.1371/journal.pone.0280677

  • Bayes-Genis, A., O. Iborra-Egea, G. Spitaleri, M. Domingo, E. Revuelta-López, P. Codina, G. Cediel, E. Santiago-Vacas, A. Cserkóová, D. Pascual-Figal, J. Núñez and J. Lupón (2021). Decoding empagliflozin's molecular mechanism of action in heart failure with preserved ejection fraction using artificial intelligence. Sci Rep,. 11(1): p. 12025.
    DOI: 10.1038/s41598-021-91546-z

  • Iborra-Egea, O., C. Gálvez-Montón, S. Roura, I. Perea-Gil, C. Prat-Vidal, C. Soler-Botija and A. Bayes-Genis (2017). Mechanisms of action of sacubitril/valsartan on cardiac remodeling: a systems biology approach. npj Systems Biology and Applications 3(12).
    DOI: 10.1038/s41540-017-0013-4

  • Lozano, M. L., C. Segú-Vergés, M. Coma, M. T. Álvarez-Roman, J. R. González-Porras, L. Gutiérrez, D. Valcárcel and N. Butta (2021). Elucidating the Mechanism of Action of the Attributed Immunomodulatory Role of Eltrombopag in Primary Immune Thrombocytopenia: An in Silico Approach. Int J Mol Sci 22, no. 13.
    DOI: 10.3390/ijms22136907

  • Segú-Vergés, C., M. Coma, C. Kessel, S. Smeets, D. Foell and A. Aldea (2021). Application of systems biology-based in silico tools to optimize treatment strategy identification in Still's disease. Arthritis Res Ther, 23(1): p. 126.
    DOI: 10.1186/s13075-021-02507-w

  • Díaz-Beyá, M., M. García-Fortes, R. Valls, L. Artigas, M. T. Gómez-Casares, P. Montesinos, F. Sánchez-Guijo, M. Coma, M. Vendranes and J. Martínez-López (2022). A Systems Biology- and Machine Learning-Based Study to Unravel Potential Therapeutic Mechanisms of Midostaurin as a Multitarget Therapy on FLT3- Mutated AML. BioMedInformatics. 2(3): p. 375-397.
    DOI: 10.3390/biomedinformatics2030024

  • Carcereny, E., A. Fernández-Nistal, A. López, C. Montoto, A. Naves, C. Segú-Vergés, M. Coma, G. Jorba, B. Oliva and J. M. Mas (2021). Head to head evaluation of second generation ALK inhibitors brigatinib and alectinib as first-line treatment for ALK+ NSCLC using an in silico systems biology-based approach. Oncotarget, 12(4): p. 316-332.
    DOI: 10.18632/oncotarget.27875

  • Segú-Vergés, C., J. Gómez., P. Terradas-Montana, L. Artigas, S. Smeets, M. Ferrer, and S. Savic (2023). Unveiling chronic spontaneous urticaria pathophysiology through systems biology. The Journal of Allergy and Clinical Immunology. 151(4): p. 1005-1014.
    DOI: 10.1016/j.jaci.2022.12.809

  • Valls, R., J. Wagg, I. Paz-Priel, G. Man, L. Artigas, G. Jaccard, M. Coma and C. Schmitt (2023). Application of systems biology to identify pharmacological mechanisms of thrombotic microangiopathy evoked by combined activated prothrombin complex concentrate and emicizumab.
    Sci Rep. 13(1): p. 10078.
    DOI: 10.1038/s41598-023-36891-x