Mechanistic computational modeling of monospecific and bispecific antibodies targeting interleukin-6/8 receptors.

The spread of cancer from organ to organ (metastasis) is responsible for the vast majority of cancer deaths; however, most current anti-cancer drugs are designed to arrest or reverse tumor growth without directly addressing disease spread. It was recently discovered that tumor cell-secreted interleukin-6 (IL-6) and interleukin-8 (IL-8) synergize to enhance cancer metastasis in a cell-density dependent manner, and blockade of the IL-6 and IL-8 receptors (IL-6R and IL-8R) with a novel bispecific antibody, BS1, significantly reduced metastatic burden in multiple preclinical mouse models of cancer. Bispecific antibodies (BsAbs), which combine two different antigen-binding sites into one molecule, are a promising modality for drug development due to their enhanced avidity and dual targeting effects. However, while BsAbs have tremendous therapeutic potential, elucidating the mechanisms underlying their binding and inhibition will be critical for maximizing the efficacy of new BsAb treatments. Here, we describe a quantitative, computational model of the BS1 BsAb, exhibiting how modeling multivalent binding provides key insights into antibody affinity and avidity effects and can guide therapeutic design. We present detailed simulations of the monovalent and bivalent binding interactions between different antibody constructs and the IL-6 and IL-8 receptors to establish how antibody properties and system conditions impact the formation of binary (antibody-receptor) and ternary (receptor-antibody-receptor) complexes. Model results demonstrate how the balance of these complex types drives receptor inhibition, providing important and generalizable predictions for effective therapeutic design.

A practical guide to combination advanced therapy in inflammatory bowel disease.

PURPOSE OF REVIEW: To provide an overview of the current literature regarding the use of advanced combination therapy (ACT) in patients with inflammatory bowel disease (IBD). Although the treatment of IBD has come a long way, many patients do not respond or will lose response to currently available treatments over time. ACT has been proposed as a model to create sustained remission in difficult-to-treat IBD patient populations. This review discusses the available literature supporting the use of ACT, followed by practical tips for applying this model of treatment to clinical practice. RECENT FINDINGS: Both observational and controlled evidence have demonstrated that there may be an increased benefit of ACT in specific IBD patient populations compared to advanced targeted immunomodulator (TIM) monotherapy. Additional data is required to understand how to best use combination TIMs and the long-term risks associated with this strategy. SUMMARY: While the literature has demonstrated the potential for benefit in both Crohn's disease and ulcerative colitis, the use of ACT is currently off-label and long-term controlled data is needed. The successful application of ACT requires careful consideration of both patient and disease profiles as well as close monitoring of treatment response and adverse events.

Examining the active ingredients of physical activity interventions underpinned by theory versus no stated theory: a meta-analysis.

In this meta-analysis, we sought to examine the 'active ingredients' (or behaviour change techniques; BCTs) used within theory-based physical activity interventions compared to interventions with no stated theory. We retrieved 171 peer-reviewed studies (224 total interventions) that used a controlled experimental design from 68 previous reviews of physical activity interventions. Data from each intervention were coded with regard to their use of theory and inclusion of 16 BCT clusters within the physical activity intervention. There were no significant differences in the overall effect sizes between theory-based (k = 148, d = 0.48) and no-stated-theory (k = 77, d = 0.37) interventions. Theory-based interventions incorporated a greater number of BCT clusters on average (6.1) compared to no-stated-theory interventions (4.5). Significant effects were shown for interventions that incorporated at least three BCT clusters (d = 0.48) but not for those that used one or two (d = 0.20). Several BCT clusters were more likely to be present in theory-based interventions than no-stated-theory interventions. Significant effects on physical activity were also shown for theory-based interventions that incorporated any of the 16 BCT clusters coded, but only for 9 out of 11 no-stated-theory interventions in this regard (for which effect sizes could be calculated). Taken together, these findings suggest that although the overall effects on physical activity do not differ significantly between theory-based and no-stated-theory interventions, these interventions often differ in their composition of BCTs. Moreover, for interventions utilising certain BCT clusters (namely, 'self-belief' and 'association'), theory may be necessary to derive significant effects.