Development of a computer-aided text message platform for user engagement with a digital Diabetes Prevention Program: a case study.

Digital Diabetes Prevention Programs (dDPP) are novel mHealth applications that leverage digital features such as tracking and messaging to support behavior change for diabetes prevention. Despite their clinical effectiveness, long-term engagement to these programs remains a challenge, creating barriers to adherence and meaningful health outcomes. We partnered with a dDPP vendor to develop a personalized automatic message system (PAMS) to promote user engagement to the dDPP platform by sending messages on behalf of their primary care provider. PAMS innovates by integrating into clinical workflows. User-centered design (UCD) methodologies in the form of iterative cycles of focus groups, user interviews, design workshops, and other core UCD activities were utilized to defined PAMS requirements. PAMS uses computational tools to deliver theory-based, automated, tailored messages, and content to support patient use of dDPP. In this article, we discuss the design and development of our system, including key requirements and features, the technical architecture and build, and preliminary user testing.

Effectiveness of an Integrated Engagement Support System to Facilitate Patient Use of Digital Diabetes Prevention Programs: Protocol for a Randomized Controlled Trial.

BACKGROUND: Digital diabetes prevention programs (dDPPs) are effective behavior change tools to prevent disease progression in patients at risk for diabetes. At present, these programs are poorly integrated into existing health information technology infrastructure and clinical workflows, resulting in barriers to provider-level knowledge of, interaction with, and support of patients who use dDPPs. Tools that can facilitate patient-provider interaction around dDPPs may contribute to improved patient engagement and adherence to these programs and improved health outcomes. OBJECTIVE: This study aims to use a rigorous, user-centered design (UCD) methodology to develop a theory-driven system that supports patient engagement with dDPPs and their primary care providers with their care. METHODS: This study will be conducted in 3 phases. In phase 1, we will use systematic UCD, Agile software development, and qualitative research methods to identify key user (patients, providers, clinical staff, digital health technologists, and content experts) requirements, constraints, and prioritization of high-impact features to design, develop, and refine a viable intervention prototype for the engagement system. In phase 2, we will conduct a single-arm feasibility pilot of the engagement system among patients with prediabetes and their primary care providers. In phase 3, we will conduct a 2-arm randomized controlled trial using the engagement system. Primary outcomes will be weight, BMI, and A1c at 6 and 12 months. Secondary outcomes will be patient engagement (use and activity) in the dDPP. The mediator variables (self-efficacy, digital health literacy, and patient-provider relationship) will be measured. RESULTS: The project was initiated in 2018 and funded in September 2019. Enrollment and data collection for phase 1 began in September 2019 under an Institutional Review Board quality improvement waiver granted in July 2019. As of December 2020, 27 patients have been enrolled and first results are expected to be submitted for publication in early 2021. The study received Institutional Review Board approval for phases 2 and 3 in December 2020, and phase 2 enrollment is expected to begin in early 2021. CONCLUSIONS: Our findings will provide guidance for the design and development of technology to integrate dDPP platforms into existing clinical workflows. This will facilitate patient engagement in digital behavior change interventions and provider engagement in patients' use of dDPPs. Integrated clinical tools that can facilitate patient-provider interaction around dDPPs may contribute to improved patient adherence to these programs and improved health outcomes by addressing barriers faced by both patients and providers. Further evaluation with pilot testing and a clinical trial will assess the effectiveness and implementation of these tools. TRIAL REGISTRATION: ClinicalTrials.gov NCT04049500; https://clinicaltrials.gov/ct2/show/NCT04049500. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/26750.

Traceless aptamer-mediated isolation of CD8+ T cells for chimeric antigen receptor T-cell therapy.

Chimeric antigen receptor T-cell therapies using defined product compositions require high-purity T-cell isolation systems that, unlike immunomagnetic positive enrichment, are inexpensive and leave no trace on the final cell product. Here, we show that DNA aptamers (generated with a modified cell-SELEX procedure to display low-nanomolar affinity for the T-cell marker CD8) enable the traceless isolation of pure CD8+ T cells at low cost and high yield. Captured CD8+ T cells are released label-free by complementary oligonucleotides that undergo toehold-mediated strand displacement with the aptamer. We also show that chimeric antigen receptor T cells manufactured from these cells are comparable to antibody-isolated chimeric antigen receptor T cells in proliferation, phenotype, effector function and antitumour activity in a mouse model of B-cell lymphoma. By employing multiple aptamers and the corresponding complementary oligonucleotides, aptamer-mediated cell selection could enable the fully synthetic, sequential and traceless isolation of desired lymphocyte subsets from a single system.

Cationic polymers for non-viral gene delivery to human T cells.

The clinical success of chimeric antigen receptor (CAR) T cell immunotherapy in treating multiple blood cancers has created a need for efficient methods of ex vivo gene delivery to primary human T cells for cell engineering. Here, we synthesize and evaluate a panel of cationic polymers for gene delivery to both cultured and primary human T cells. We show that a subset of comb- and sunflower-shaped pHEMA-g-pDMAEMA polymers can mediate transfection with efficiencies up to 50% in the Jurkat human T cell line with minimal concomitant toxicity (>90% viability). We then optimize primary human T cell transfection conditions including activation time, cell density, DNA dose, culture media, and cytokine treatment. We demonstrate transfection of both CD4+ and CD8+ primary human T cells with messenger RNA and plasmid DNA at efficiencies up to 25 and 18%, respectively, with similarly high viability.

Targeted delivery of proapoptotic peptides to tumor-associated macrophages improves survival.

Most current cancer therapies focus on killing malignant cells, but these cells are often genetically unstable and can become resistant to chemotherapy. Tumor-associated macrophages (TAMs) facilitate disease progression by promoting angiogenesis and tumor cell growth, as well as by suppressing the adaptive immune response. TAMs are therefore potential targets for adjuvant anticancer therapies. However, resident macrophages are critical to host defense, and preferential ablation of TAMs remains challenging. Macrophage activation is broadly categorized as classically activated, or M1, and alternatively activated, or M2, and TAMs in the tumor microenvironment have been shown to adopt the anti-inflammatory, M2-like phenotype. To date, there are no methods for specific molecular targeting of TAMs. In this work, we report the discovery of a unique peptide sequence, M2pep, identified using a subtractive phage biopanning strategy against whole cells. The peptide preferentially binds to murine M2 cells, including TAMs, with low affinity for other leukocytes. Confocal imaging demonstrates the accumulation of M2pep in TAMs in vivo after tail vein injection. Finally, tail vein injection of an M2pep fusion peptide with a proapoptotic peptide delays mortality and selectively reduces the M2-like TAM population. This work therefore describes a molecularly targeted construct for murine TAMs and provides proof of concept of this approach as an anticancer treatment. In addition, M2pep is a useful tool for murine M2 macrophage identification and for modulating M2 macrophages in other murine models of disease involving M2 cells.