ATTD 2018 Invited Speaker Abstracts A-1 ATTD 2018 Oral Abstracts A-11 ATTD 2018 E-Poster Discussion Abstracts A-36 Downloaded by 187.178.95.102 from www.liebertpub.com at 04/09/18. For personal use only. ATTD 2018 E-Poster Viewing Abstracts A-48 ATTD 2018 Read By Title A-149 ATTD 2018 Abstract Author Index A-153 DIABETES TECHNOLOGY & THERAPEUTICS Volume 20, Supplement 1, 2018 ª Mary Ann Liebert, Inc. DOI: 10.1089/dia.2018.2525.abstracts ATTD 2018 ABSTRACTS ATTD 2018 Invited Speaker Abstracts 001 Clinicians are frequently confronted with discrepancies be- tween glucose values as noted by patients in their diaries and OPENING CEREMONY HbA1c values. Also in the CGM era, such discrepancies are still ATTD8-0442 seen. A number of explanations can co-exist. One of these is the glycation gap, the variation in HbA1c that can be seen between BEYOND A1C: CONSENSUS ON CGM OUTCOMES patients with identical mean glucose values. Whether this is more T. Danne1 than a mathematical phenomenon has been debated extensively over the years. More recently, the glycation gap has been pro- 1 Kinder- und Jugendkrankenhaus AUF DER BULT, Dep. of posed as a possible explanation for the ACCORD findings. All General Pediatrics-Diabetes-Endocrinology & Clinical this will be put in perspective in this talk. Reserach, Hannover, Germany Recently several panels of physicians, researchers, regulators 003 and individuals with diabetes who are experts in continuous glucose monitoring (CGM) technologies addressed the issue NEXT GENERATION SOLUTIONS how to move beyond the HbA1c measurement as the sole marker ATTD8-0446 of glycemic control. Although HbA1c has proved extremely valuable in for patient management, is a valuable measure of DEALING WITH PATIENT AND DEVICE population health and remains a validated indicator of glycation UNCERTAINTY IN THE ARTIFICIAL PANCREAS: as a risk factor for complications, it is not as helpful for per- MULTI-ZONES, ADAPTATION, AND TRUST INDICES sonalized diabetes management. The recently published ATTD F.J. Doyle1 consensus recommendations represent the current understand- ing of how CGM results can affect outcomes. CGM, either from 1Harvard University, School of Engineering and Applied real-time use (rtCGM) or intermittently-viewed continuous Sciences, Cambridge, USA glucose monitoring (iCGM), address many of the limitations inherent in HbA1c testing and SMBG. The reliable identifica- There have been well over 100 closed-loop clinical trials for tion of hypoglycemia is just as important as the measurement of the artificial pancreas (AP), in one form or another, over the last time in range (70–180 mg/dl [3.9–10.0 mmol/L]) in clinical decade. Commercial devices have also begun to emerge in the trials. Quantifying the duration and extent of glycemic excur- last year. Yet, in many respects, we have only scratched the sions and glycemic variability (by Coefficient of Variation, surface on algorithms for the AP as most of the current studies which defines stable glucose levels as CV <36%) provides an- focus on fairly traditional implementations of fuzzy logic, PID, other parameter for assessing glucose control. In clinical prac- or MPC control systems. In this talk I will highlight recent al- Downloaded by 187.178.95.102 from www.liebertpub.com at 04/09/18. For personal use only. tice, the advanced metrics of assessing continuous glucose data gorithm engineering results, including preliminary clinical data, are appropriate as outcome parameters that complement HbA1c on the next wave of algorithms that address the intrinsic uncer- for a wide range of patients with diabetes and should be con- tainty in the patient-device feedback loop. These include ex- sidered for use to help them improve glycemic control provided tensions of our successful zone MPC design to address multiple that appropriate educational and technical support is available. distinct zones and trust indices. CGM is also a robust research tool, and CGM data should be recognized by governing bodies as a valuable and meaningful endpoint to be used in clinical trials of new drugs and devices for 004 diabetes treatment. NEXT GENERATION SOLUTIONS 002 ATTD8-0447 GLUCOSE METRICX: BEYOND HBA1C NEXT GENERATION AUTOMATED INSULIN DELIVERY: ON-BODY ECOSYSTEM FOR ATTD8-0439 AUTOMATED INSULIN DELIVERY GLYCATION GAP: DOES IT EXIST? IN TYPE 1 DIABETES H. De Vries1 E. Dassau1 1Academic Medical Center at the University of Amsterdam, 1Harvard University, Harvard John A. Paulson School of Endocrinology, Amsterdam, The Netherlands Engineering and Applied Sciences, Cambridge, USA A-1 A-2 ATTD 2018 INVITED SPEAKER ABSTRACTS Fully automated glucose management technologies for type 1 3. Generate data able to satisfy safety and efficacy re- diabetes (T1D) require advanced sensing and decision-support to quirements by regulatory agencies regarding the clin- function safely, intelligently, and efficiently. Recent academic ical testing of artificial pancreas device systems in the studies as well as early commercial devices have shown to be target population of people with type 1 diabetes. safe and effective in managing glucose across different chal- lenges and in outpatient settings. The iDCL Trial runs in 7 research sites in the U.S. and 3 sites New developments in wearable and embedded technology, in Europe coordinated by the Jaeb Center for Health Research. big data, fog and edge computing, wireless networks and cloud iDCL Protocol 1 is a trial of mobile closed-loop control using a computing, provide a unique opportunity to enhance automation, smart phone to run the control algorithm and communicate with manage therapeutic strategies and improve quality of care in subcutaneous continuous glucose monitor (CGM) and an insulin people with T1D by exploiting real-time medical information pump. Protocol 2 uses a mobile system as well, but the CGM is from a vast collection of sensors: the medical internet-of-things expected to be an implantable device. Protocol 3 is testing a (mIoT). In this talk I will highlight recent developments to enable hardware configuration in which the control algorithm is em- on-Body Ecosystem including a new platform to support the bedded in the insulin pump. First data from the active protocols clinical investigation of mIoT, results of fully embedded control will be presented. design on a chip and strategies to integrate mIoT in diabetes research and clinical studies. 007 BIOTECHNOLOGY AND DIABETES 005 ATTD8-0443 DEBATE: PUMP V. SENSOR – WHAT IS MORE IMPORTANT POST-TRANSPLANT DIABETES IN CHILDREN AND ADOLESCENTS ATTD8-0438 M. Sperling1 SENSORS 1Professorial Lecturer-Icahn School of Meicine at Mount Sinai, H. De Vries1 Pediatric Endocrinology and Diabetes, New York, USA 1Academic Medical Center at the University of Amsterdam, POST-TRANSPLANT DIABETES IN ADOLESCENTS Endocrinology, Amsterdam, The Netherlands Post-transplant diabetes (PTDM) is an increasingly recog- nized and common consequence of solid organ transplantation, Drs Leelarathna and DeVries will debate on the pro’s and cons present in the majority in the immediate post-operative period of insulin pump therapy in the age of continuous glucose mon- and persisting as ‘‘permanent’’ diabetes in about 12%–15% of itoring. Continuous glucose monitoring seems to establish itself transplant recipients. The immediate precipitating factors are the as the standard of care. What, if any, is the role of insulin pumps immunosuppressive agents; the calcineurin inhibitors cyclo- nowadays? sporine and tacrolimus, the molecular target of Rapamycin (mTOR) inhibitors sirolimus and everolimus, and high dose 006 steroids. Together, these agents combine to exert toxic effects on beta cells, induce hypomagnesemia, impair insulin secretion, CLOSING THE LOOP - NIH-FUNDED AP RESEARCH and induce insulin resistance, magnified by the inflammatory EFFORTS stressors of surgery. In addition, a family history and identified ATTD8-0452 SNPs associated with T1DM, T2DM, and MODY suggest a genetic predisposition in those who go on to permanent DM after THE INTERNATIONAL DIABETES CLOSED-LOOP the acute high doses of immuno-suppressive drugs used to (IDCL) TRIAL manage rejection are reduced. The criteria applied to diagnose Downloaded by 187.178.95.102 from www.liebertpub.com at 04/09/18. For personal use only. DM are based on glucose concentrations as defined by the B. Kovatchev1 American Diabetes Association and/or the International Diabetes 1University of Virginia, Center for Diabetes Technology, Federation; HbA1c measurements should not be used to diagnose Charlottesville, USA PTDM because they are unreliable in the post-operative patient receiving blood products. PTDM may interfere with post- The iDCL Trial is supported by NIH/NIDDK grant UC4 DK operative healing and recovery and predisposes the patient to 108483. This project includes three parallel protocols testing infections, particularly HCV and CMV viral infections. Sepsis is different hardware implementations of the inControl closed-loop more likely in those with poorly controlled PTDM. The source of algorithm originally developed at the University of Virginia and the donor organ also influences the subsequent development of then refined by TypeZero Technologies, Inc. A fourth protocol is PTDM; e.g. cadaveric kidney organs, related or unrelated to the planned for 2018 to test a control algorithm developed at Harvard recipient, are more likely to be associated with PTDM than or- University. The objectives of the iDCL Trial are to: gans from living donors, and this has been attributed to higher levels of pro-inflammatory