Drug-regulated CD33-targeted CAR T cells control AML using clinically optimized rapamycin dosing.

Chimeric antigen receptor (CAR) designs that incorporate pharmacologic control are desirable; however, designs suitable for clinical translation are needed. We designed a fully human, rapamycin-regulated drug product for targeting CD33+ tumors called dimerizaing agent-regulated immunoreceptor complex (DARIC33). T cell products demonstrated target-specific and rapamycin-dependent cytokine release, transcriptional responses, cytotoxicity, and in vivo antileukemic activity in the presence of as little as 1 nM rapamycin. Rapamycin withdrawal paused DARIC33-stimulated T cell effector functions, which were restored following reexposure to rapamycin, demonstrating reversible effector function control. While rapamycin-regulated DARIC33 T cells were highly sensitive to target antigen, CD34+ stem cell colony-forming capacity was not impacted. We benchmarked DARIC33 potency relative to CD19 CAR T cells to estimate a T cell dose for clinical testing. In addition, we integrated in vitro and preclinical in vivo drug concentration thresholds for off-on state transitions, as well as murine and human rapamycin pharmacokinetics, to estimate a clinically applicable rapamycin dosing schedule. A phase I DARIC33 trial has been initiated (PLAT-08, NCT05105152), with initial evidence of rapamycin-regulated T cell activation and antitumor impact. Our findings provide evidence that the DARIC platform exhibits sensitive regulation and potency needed for clinical application to other important immunotherapy targets.

Impact of electronic alerts for acute kidney injury on patient outcomes: interrupted time-series analysis of population cohort data.

BACKGROUND: Automated acute kidney injury (AKI) electronic alerts (e-alerts) are rule-based warnings triggered by changes in creatinine and are intended to facilitate earlier detection in AKI. We assessed the impact of the introduction in the Tayside region of UK in April 2015 of automated AKI e-alerts with an accompanying education programme. METHODS: Interrupted time-series analysis using segmented regression was performed involving all adults with AKI aged ≥18 years who had a serum creatinine measured between 1 April 2013 and 31 March 2017. Analysis evaluated associations of AKI e-alert introduction on rate and severity (Stages 2-3) of AKI as well as mortality and occupied hospital bed days per patient per month in the population with AKI. RESULTS: There were 32 320 episodes of AKI during the observation period. Implementation of e-alerts had no effect on the rate of any AKI [incidence rate ratio (IRR) 0.996, 95% confidence interval (CI) 0.991 to 1.001, P = 0.086] or on the rate of severe AKI (IRR 0.995, 95% CI 0.990 to 1.000, P = 0.061). Subgroup analysis found no impact on the rate or severity of AKI in hospital or in the community. Thirty-day mortality following AKI did not improve (IRR 0.998, 95% CI 0.987 to 1.009, P = 0.688). There was a slight reduction in occupied bed days (ß-coefficient -0.059, 95% CI -0.094 to -0.025, P = 0.002). CONCLUSIONS: Introduction of automated AKI e-alerts was not associated with a change in the rate, severity or mortality associated with AKI, but there was a small reduction in occupied hospital bed days.

Assessing the accuracy of ICD-10 coding for measuring rates of and mortality from acute kidney injury and the impact of electronic alerts: an observational cohort study.

BACKGROUND: The application of a uniform definition for acute kidney injury (AKI) is vital to advance understanding and management of AKI. International Classification of Diseases (Tenth Revision) (ICD-10) coding is frequently used to define AKI, but its accuracy is unclear. The aim of this study was to determine whether ICD-10 coding is a reliable method of monitoring rates and outcomes of AKI in inpatients compared with biochemically defined AKI, and whether electronic alerts (e-alerts) for AKI affect ICD-10 AKI coding. METHODS: An observational cohort study of all 505 662 adult admissions to acute hospitals in two Scottish Health Boards [National Health Service (NHS) Tayside and NHS Fife] from January 2013 to April 2017 was performed. AKI e-alerts were implemented in NHS Tayside in April 2015. Sensitivity, specificity, positive and negative predictive values of ICD-10 coding for AKI compared with biochemically defined AKI using the Kidney Disease: Improving Global Outcomes definition and relative risk of 30-day mortality in people with ICD-10 and biochemically defined AKI before and after AKI e-alert implementation were performed. RESULTS: Sensitivity of ICD-10 coding for identifying biochemically defined AKI was very poor in both health boards for all AKI (Tayside 25.7% and Fife 35.8%) and for Stages 2 and 3 AKI (Tayside 43.8% and Fife 53.8%). Positive predictive value was poor both for all AKI (Tayside 76.1% and Fife 45.5%) and for Stages 2 and 3 AKI (Tayside 45.5% and Fife 36.8%). Measured mortality fell following implementation of AKI e-alerts in the ICD-10-coded population but not in the biochemically defined AKI population, reflecting an increase in the proportion of Stage 1 AKI in ICD-10-coded AKI. There was no evidence that the introduction of AKI e-alerts in Tayside improved ICD-10 coding of AKI. CONCLUSION: ICD-10 coding should not be used for monitoring of rates and outcomes of AKI for either research or improvement programmes.

Care bundles for acute kidney injury: a balanced accounting of the impact of implementation in an acute medical unit.

In 2009, a National Confidential Enquiry into Patient Outcome and Death report detailed significant shortcomings in recognition and management of patients with acute kidney injury (AKI). As part of a national collaborative to reduce harm from AKI, the Scottish Patient Safety Programme developed two care bundles to improve response ('SHOUT') and review ('BUMP') of AKI. Baseline data from eight patients with AKI on the acute medical unit (AMU) in Ninewells Hospital showed 62% compliance with SHOUT. However, most patients were transferred from AMU within 24 hours so BUMP could not be assessed. Our aim was to achieve >95% compliance with SHOUT on AMU within 2 months. The content of the SHOUT bundle was condensed onto a sticker for the case notes, which was implemented using Plan-Do-Study-Act cycles. Compliance was assessed weekly and feedback obtained from stakeholders concerning their opinion of the sticker, SHOUT bundle and care bundles in general. Use of the sticker was 27% in week 1 but fell to 5% by week 4. Compliance with the bundle varied from 45% to 60% and was only slightly improved by use of the sticker (OR 1.58, 95% CI 0.39 to 6.42). Staff found the sticker burdensome and did not agree that all elements of SHOUT were equally important. This opinion was supported by finding that their compliance with sepsis and hypovolaemia recommendations was 91%-100% throughout, whereas urinalysis was documented in only 55%-63% of patients. Several staff mentioned 'bundle fatigue' and on one day we identified 22 other care bundles or structured improvement forms in AMU. We concluded that the AMU staff had legitimate concerns about the SHOUT care bundle and that our intervention was demotivating. Overcoming bundle fatigue will not be a simple task. We plan to work with staff on integrating AKI into patient safety huddles and on using modelling and recognition of good practice to improve motivation.