Funded Projects

The ACT NOW Eat, Sleep, Console (ESC) Clinical Trial approach to the management of neonatal opioid withdrawal syndrome (NOWS) emphasizes parental involvement, simplifies the assessment of infants with NOWS and focuses interventions on non-pharmacologic therapies. Although outcomes following implementation of the ESC care approach, inclusive of the ESC Care Tool, appear promising and initial accounts suggest that it is safe, there has yet to be a rigorous randomized clinical trial to demonstrate the safety, efficacy and generalizability of its use in the care of infants with NOWS. The ESC Clinical Trial leverages the infrastructure and collaborations of the Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network and the IDeA States Pediatric Clinical Trials Network to reach the populations most affected by the opioid epidemic. The trial will provide answers to numerous critical gaps in our knowledge with respect to the best practices for the identification and management of infants with NOWS, as well as our understanding of the outcomes of these infants.

Neonatal Opioid Withdrawal Syndrome (NOWS) is a condition that occurs when newborns are exposed to opioids during pregnancy. Symptoms often include tremors, excessive crying, sleep deprivation, and swallowing difficulties. Cases are rising, with a newborn affected by NOWS approximately every 15 minutes. Currently, healthcare providers in the United States lack standard, evidence-based treatments for NOWS. 

This project is part of a multi-center, randomized controlled clinical trial that directly compares NOWS treatments—morphine, methadone, and buprenorphine—and takes into account other types of non-drug therapies, such as behavioral interventions. The goal is to generate results that can inform clinical practice guidelines and give newborns with NOWS the best start possible. 

This site includes newborn nurseries and intensive care nurseries at 4 large
maternity centers across the Children’s Hospital of Philadelphia (CHOP) Newborn Care Network, each with a dedicated follow-up clinic, ensuring access to a large and diverse patient population for long-term study. CHOP also has a long history of successfully conducting multi-center clinical studies.

Rapid technological advances are leading to field-deployable mobile sensing devices that can quantify complex dynamics of key physical, biological, behavioral, social, and environmental factors, enabling us to understand causation in complex disorders. Significant new investment is needed to develop and disseminate data analytics tools. The Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K) will generate generalizable theory, methods, tools, and software to address major barriers to processing complex mobile sensor data and its use in biomedical knowledge discovery and just-in-time care delivery. We will develop and implement a standards-based, interoperable, extensible, and open-source big data software platform for efficient implementation of MD2K data analytics. MD2K will demonstrate the feasibility, utility, and generalizability of this approach by implementing the entire MD2K data analytics system in the context of two biomedical applications: reducing relapse among abstinent daily smokers and reducing readmission among congestive heart failure patients

High rates of relapse and overdose deaths pose significant challenges to the treatment of Opioid Use Disorder (OUD). Anti-opioid immunotherapies (i.e., vaccines and monoclonal antibodies) have great potential to reduce long-term opioid use and overdose, with minimal risk of side effects, when used in conjunction with pharmacological treatments and/or behavioral therapies. The ability of an anti-opioid vaccine to induce antibodies that render an opioid less effective, or less rewarding, and protect from accidental overdose could provide an important therapeutic option for patients undergoing treatment for OUD. The goal of this collaborative study is to design, develop, and evaluate vaccines for use in the treatment of opioid use disorder

Social big data analysis of publicly available user data on social media platforms is a promising approach for attaining organic observations of behavior that can monitor and predict real-world public health problems, such as HIV incidence. In preliminary research, our team identified and collected tweets suggesting HIV risk behaviors (e.g., drug use, high-risk sexual behaviors), modeled them alongside CDC statistics on HIV diagnoses, and found a significant positive relationship between HIV-related tweets and county-level HIV cases. We propose to create a single automated platform that collects social media data, identifies and labels tweets that suggest HIV-related behaviors, and predicts regional HIV incidence. We will interview staff and participants at local and regional HIV organizations to understand ethical issues associated with mining people’s data. The software developed from this application will be shared with HIV researchers and health care workers to combat the spread of HIV.

There is a great deal of research aimed at better understanding transitions in alcohol and other drug (AOD) use patterns from early to late adolescence and from late adolescence to emerging adulthood. However, no studies to date have (a) assessments of AOD use from ages 10 to 24 across all developmental periods (middle school, high school, and emerging adulthood); (b) a large sample with substantial racial and ethnic diversity, particularly among Hispanic and Asian youth; (c) in-depth coverage of 10 areas of functioning across three key domains; (d) subjective and objective neighborhood data; or (e) the capacity to examine developmental trajectories for more than one substance. The current proposal is a continuation of previous projects that assessed AOD use across nine waves of data from age 10 to age 19. The proposed study capitalizes on the longitudinal data on protective and risk factors we have collected since age 10 in an ethnically diverse cohort by continuing to annually assess these youth in order to capture important transitions to emerging adulthood (through age 24). By advancing the epidemiology of alcohol use during adolescence and emerging adulthood, our findings can affect prevention and intervention programming for young people and address critical issues of public health policy.

Profound sleep disturbances during abstinence have long been suspected of perpetuating vulnerability to relapse of people who misuse or are addicted to opioids. An animal model has shown that long-term sleep deficiency results in a persistent state of physiological dysregulation that is expected to modify the biology of abstinence and increase relapse potential. This study seeks to discover how persistent sleep restriction during withdrawal from opioid use increases vulnerability to relapse in the animal model by testing whether persistent sleep restriction during abstinence from opioid use is sufficient to increase opioid drug seeking. The functional outcome measure will be the degree of mitigation of opioid seeking. These studies will provide a basis for novel translational approaches to target mechanisms that are demonstrated to cause increased vulnerability to relapse.

Chronic pain and opioid use disorders (OUD) are burgeoning interrelated epidemics. Sleep disturbances are prevalent, treatable, and increasingly recognized as risk factors for both chronic pain and OUD. Sleep disruption impairs endogenous pain inhibition, linked to analgesic efficacy and rewarding properties of mu-opioid receptor (MOR) agonists. It is not known, however, whether sleep disturbance causally alters mechanisms that contribute to OUD risk. Sleep continuity disruption (SCD) and/or sleep fragmentation (SF) may alter cerebral MOR availability, and these forms of sleep disruption may increase OUD risk. This study aims to 1) evaluate whether experimental SCD and/or SF alter resting or pain-evoked MOR binding potential (BP) in brain regions associated with pain inhibition; 2) examine whether SCD and/or SF alters the analgesic response; and 3) determine whether MOR BP in brain regions of interest are associated with analgesia and abuse liability.

Opioid use disorder (OUD) is a chronic and relapsing brain disease that affects over 2 million Americans. Despite effective evidence-based treatments in the form of behavioral interventions and FDA-approved medication for addiction treatment (MAT), relapse rates are high. The Collaboration Linking Opioid Use Disorder and Sleep Study will investigate patients on MAT to elucidate potential causal mechanisms between sleep deficiency and OUD. The aims of this study are to 1) test whether there are different neurocognitive connectivity patterns between patients with adequate vs. deficient sleep in brain systems involved in addiction and assess the extent to which these “neural fingerprints” predict ongoing opioid use; 2) evaluate the potential biologic, psychiatric, and pharmacologic mechanisms that explain the causal pathway between sleep deficiency and opioid use; and 3) test ecologic factors such as psychosocial, family, and neighborhood contextual factors associated with OUD and their contribution to sleep deficiency among patients in MAT.

For individuals with moderate to severe opioid use disorder (OUD), medication-assisted treatments (MATs) such as oral methadone and extended-release naltrexone (XR-NTX) are the gold standard in initiating and maintaining long-term recovery. Still, many patients struggle with persistent sleep disturbance and stress reactivity in the early stages of recovery, which drive relapse behaviors. This proposal constitutes a novel mechanistic approach to understanding the role of the orexin system in sleep disturbance and circadian rhythms of stress in OUD patients who are maintained on MATs and are early in recovery. This study will determine whether the FDA-approved sleep medication suvorexant (SUVO) improves sleep continuity and decreases diurnal measures of stress, and whether improvement of sleep/stress processes translates to improved OUD treatment outcomes. Its findings will fill critical gaps in our understanding of the role of the orexin system in sleep disturbance and circadian rhythms of stress that impact OUD recovery.

Among the most common symptoms experienced by individuals suffering with opioid use disorder (OUD) are severe sleep and circadian disruptions. The relationship between opioid dependence and sleep and circadian systems is not well understood. A circadian-dependent mechanism has been shown to modulate fentanyl reward-related behaviors in the nucleus accumbens (NAc). The study team will use a combination of behavioral, slice electrophysiology, and molecular approaches to 1) investigate the role of the circadian transcription factor NPAS2 in medium spiny neurons with dopamine 1 (D1R-MSNs); 2) assess the impact of fentanyl on synaptic plasticity at D1R-MSNs and investigate whether NPAS2 mediates the potentiation of excitatory synapses at specific diurnal phases; 3) elucidate the cell-type-specific NPAS2-dependent transcriptional mechanisms of fentanyl-seeking and relapse behaviors; and 4) investigate whether NPAS2 rescue and buprenorphine medication-assisted treatment (MAT) improve fentanyl-induced sleep disturbances. This study will define the role for circadian-dependent transcriptional mechanisms and uncover the therapeutic potential of NPAS2 for opioid dependence and relapse.

Medications for the treatment of opioid use disorders (MOUD) are effective at reducing opioid use, opioid overdose risk, and opioid-related deaths; however, retention and adherence to MOUD treatment, particularly buprenorphine (BUP), are discouragingly low. The objective of the current research is to adapt and extend a cognitive behavioral therapy-based short message system (SMS) intervention (TXT-CBT) to address MOUD treatment retention and adherence using the imFREE (Interactive Messaging for Freedom from Opioid Addiction) platform. imFREE builds upon the efficacious SMS-based TXT-CBT intervention, with content addressing retention and adherence to BUP, including mitigating risk factors for dropout, and features to notify social and provider support contacts in the face of treatment discontinuation and/or other indicators of relapse and overdose risk. By providing support to maximize BUP treatment adherence, coupled with skills to prevent relapse, imFREE may provide a cost-effective, easily deployable strategy for OUD treatment and prevention of overdose deaths.

This application will develop and execute a sequential multiple assignment randomized trial (SMART) design to test two forms of behavioral economics intervention to promote medication-assisted treatment (MAT) for opioid use disorder. The two interventions, in person, brief motivational interviewing and substance-free activities intervention (BMI+SFAS), initially will be tested for satisfaction and acceptability with participants who are initiating buprenorphine-naloxone treatment and then be tested by SMART for its ability to promote MAT adherence. This innovative SMART design that tests two psychosocial interventions to increase adherence to MAT initiation is likely to have a significant impact on engagement of opioid use disorder patients in treatment and address an underserved population with opioid use disorder who is resistant to MAT adherence.