Barriers to childhood vaccination in urban slums of Pakistan.

Background: The urban slums of Pakistan continue to record low childhood vaccination coverage. It is therefore vital to understand the demand-side barriers to childhood vaccination in the slums to determine the required demand-generation interventions. Aims: To document the demand-side barriers related to childhood vaccination in urban slums of Pakistan and recommend appropriate demand-generation interventions. Methods: We investigated the demand-side barriers to childhood vaccination in 4 urban slums of Karachi, Pakistan, and disseminated the findings to the Expanded Program on Immunization and their partners. Using the findings, we made recommendations for collaborations with the various partners and for the design of demand-generation interventions to address the barriers. We then expanded the scope of the original research through a mapping exercise that gathered information on the vaccination-related research and interventions of the partners and used the information gathered to create a portfolio of activities. We present the demand-side barriers from the original research and the portfolio of demand-generation interventions. Results: The original research showed that 412 (49.0%) children aged 12-23 months, from 840 households, were fully vaccinated. Reasons given for not receiving the recommended vaccinations were mainly related to the fear of side effects, social and religious influences, lack of awareness, and misconceptions about vaccine administration. The mapping of activities revealed 47 initiatives that aimed to generate demand for childhood vaccination in the urban slums of Pakistan. Conclusion: Several stakeholders involved in childhood vaccination in the urban slums of Pakistan act independently, operating programmes that are disconnected. There is a need for better coordination and integration of the childhood vaccination interventions by these partners to achieve the goal of universal vaccination coverage.

A Personalized Therapeutics Approach Using an In Silico Drosophila Patient Model Reveals Optimal Chemo- and Targeted Therapy Combinations for Colorectal Cancer.

In silico models of biomolecular regulation in cancer, annotated with patient-specific gene expression data, can aid in the development of novel personalized cancer therapeutic strategies. Drosophila melanogaster is a well-established animal model that is increasingly being employed to evaluate such preclinical personalized cancer therapies. Here, we report five Boolean network models of biomolecular regulation in cells lining the Drosophila midgut epithelium and annotate them with colorectal cancer patient-specific mutation data to develop an in silico Drosophila Patient Model (DPM). We employed cell-type-specific RNA-seq gene expression data from the FlyGut-seq database to annotate and then validate these networks. Next, we developed three literature-based colorectal cancer case studies to evaluate cell fate outcomes from the model. Results obtained from analyses of the proposed DPM help: (i) elucidate cell fate evolution in colorectal tumorigenesis, (ii) validate cytotoxicity of nine FDA-approved CRC drugs, and (iii) devise optimal personalized treatment combinations. The personalized network models helped identify synergistic combinations of paclitaxel-regorafenib, paclitaxel-bortezomib, docetaxel-bortezomib, and paclitaxel-imatinib for treating different colorectal cancer patients. Follow-on therapeutic screening of six colorectal cancer patients from cBioPortal using this drug combination demonstrated a 100% increase in apoptosis and a 100% decrease in proliferation. In conclusion, this work outlines a novel roadmap for decoding colorectal tumorigenesis along with the development of personalized combinatorial therapeutics for preclinical translational studies.