The challenges associated with conducting central nervous system clinical research all impact sponsors’ and study teams’ ability to gather stronger therapeutic evidence—but they also prime CNS studies for decentralization.
Common obstacles in CNS research include:
These challenges all impact sponsors’ and study teams’ ability to gather stronger therapeutic evidence—but they also prime CNS studies for decentralization.
Let’s dive into how decentralized clinical trials (DCTs), leveraging a modular approach, can address four key challenges in central nervous system research to reduce participant uncertainty and burden, increase participant compliance, and drive data quality.
Recruitment and retention in clinical studies for CNS diseases has become a major challenge for sponsors and the research teams who run these studies. As a result, CNS trials confront more frequent delays than those in other therapeutic areas, with associated increased costs.
According to research in Applied Clinical Trials, “[t]he reason for this is … smaller population[s] of patients compared to other indications,” as well as “the complicated and lengthy nature of these trials and the unique features of CNS diseases such as the mental dependency of patients suffering with neurodegenerative diseases.”
CNS disorders and health conditions can limit patients’ mobility, energy, and cognitive abilities, inhibiting—or even prohibiting—travel to and from clinical research sites and increasing their need for streamlined participant-facing tools and support.
In effect, many patients who stand to benefit the most from the development of a new CNS treatment or drug also confront the biggest barriers to study participation.
DCTs can bring CNS clinical trials directly to patients and their caregivers, addressing many of the barriers associated with patient recruitment and retention:
By reducing the participant burden from start to finish, DCT and hybrid clinical trial models broaden the pool of potential participants while also providing the support, tools and resources, and flexible processes patients need to supply quality data. This, in turn, supports better insights and, ultimately, stronger therapeutic evidence.
Much like reproductive and women’s health, many CNS conditions are still considered “taboo,” both on a cultural level and by patients themselves. Some potential participants may hesitate to enroll because of concerns about disclosing personal health information, being judged, stereotyped, or negatively labeled. And, patients who have enrolled may be performative in their responses or withhold information for the same reasons.
When discussing sensitive health topics during CNS studies, participants can benefit from interacting with clinicians and researchers through a screen rather than face-to-face. With remote methods like telehealth and mobile chat features, patients who desire it can achieve a comfortable distance from the study team—close enough to complete check-ins and access healthcare support when needed, but removed enough to be discreet.
Similarly, the ability to respond to questionnaires, submit outcomes, and update health status remotely may encourage patients to be more honest and accurate in their reporting. With stressors—such as unfamiliar clinics and new clinicians—reduced or removed, patients are able to submit real-time, real-world data without having to confront situations that may bias that data.
Patient- and clinician-reported outcomes provide the basis for measuring most endpoints in CNS clinical trials. For example, in a clinical trial for depression, clinicians may leverage scales—such as the Montgomery-Åsberg Depression Rating Scale (MADRS)—to assess depressive symptom changes in patients. In the same study, participants may personally rate their symptoms, such as the severity of an anxiety attack or the quality of their sleep.
While these outcomes are important to capture, they are also prone to recall bias or skewed perceptions—particularly when there’s a long waiting period between experiencing and reporting a symptom. There is also the concern of variability within the expert rating process, which is subject to human error and can further impact data quality.
Achieving 100% objective reporting isn’t the goal of every CNS clinical trial. Some studies may require a combination of subjective and objective data, depending on chosen endpoints. But, wherever objective data is needed, leveraging technology to support humans can drive more accurate, consistent results.
Although not typically associated with CNS clinical development programs, sensors and wearables can serve as important tools for gathering continuous or point-in-time data. These data points—such as heart rate, step tracking, or sleep tracking—can be used to objectively measure symptom severity while also contextualizing patients’ own assessments of their symptoms.
More common to current CNS research are ePRO and eClinRo (electronic clinician-reported outcomes), which allow participants and clinicians to submit real-time data on behaviors and symptoms. For patients in particular, ePRO allows them to:
Meanwhile, an electronic clinical outcome assessment (eCOA) platform streamlines the expert review process, augmenting expert assessments by:
Whether they’re leveraged individually or together, all of these tools provide increased data accuracy to support stronger evidence and proof of efficacy.
In CNS clinical trials, the stakes can be extremely high. This research focuses on critical functions within the brain and nervous system. As a result, maintaining communication with patients and encouraging their engagement is essential—both for study outcomes and for ensuring patients’ safety. Participants who are out of compliance or who drop out entirely pose a major concern for study teams.
DCT and hybrid studies incorporate patient-centric processes, intuitive digital tools, and ongoing support to keep participants engaged throughout the study. These models use human-centric design to meet patients’ needs with flexibility while also ensuring their safety, including:
Well-designed DCTs don’t replace the human component of clinical research—they simply support humans in new ways at every stage of the trial.
More than 4,000 CNS clinical trials are expected to be underway by 2026, according to Evaluate Pharma. And, these trials require new approaches, according to researchers writing in the journal Therapies: “Central nervous system disorders remain the leading causes of mortality and morbidity worldwide, affecting more than 1 billion patients,” the authors indicate. “This therapeutic area suffers from high unmet medical needs and the search for innovative approaches to identify therapeutic strategies is urgent in the field.”
The potential for DCT models within CNS research can meet this urgency—with broad applications. By providing a multi-pronged solution, DCTs can address many of the challenges inherent in CNS trials, ultimately delivering stronger evidence and accelerating the speed to market for life-changing new treatments.
Common obstacles in CNS research include:
These challenges all impact sponsors’ and study teams’ ability to gather stronger therapeutic evidence—but they also prime CNS studies for decentralization.
Let’s dive into how decentralized clinical trials (DCTs), leveraging a modular approach, can address four key challenges in central nervous system research to reduce participant uncertainty and burden, increase participant compliance, and drive data quality.
Recruitment and retention in clinical studies for CNS diseases has become a major challenge for sponsors and the research teams who run these studies. As a result, CNS trials confront more frequent delays than those in other therapeutic areas, with associated increased costs.
According to research in Applied Clinical Trials, “[t]he reason for this is … smaller population[s] of patients compared to other indications,” as well as “the complicated and lengthy nature of these trials and the unique features of CNS diseases such as the mental dependency of patients suffering with neurodegenerative diseases.”
CNS disorders and health conditions can limit patients’ mobility, energy, and cognitive abilities, inhibiting—or even prohibiting—travel to and from clinical research sites and increasing their need for streamlined participant-facing tools and support.
In effect, many patients who stand to benefit the most from the development of a new CNS treatment or drug also confront the biggest barriers to study participation.
DCTs can bring CNS clinical trials directly to patients and their caregivers, addressing many of the barriers associated with patient recruitment and retention:
By reducing the participant burden from start to finish, DCT and hybrid clinical trial models broaden the pool of potential participants while also providing the support, tools and resources, and flexible processes patients need to supply quality data. This, in turn, supports better insights and, ultimately, stronger therapeutic evidence.
Much like reproductive and women’s health, many CNS conditions are still considered “taboo,” both on a cultural level and by patients themselves. Some potential participants may hesitate to enroll because of concerns about disclosing personal health information, being judged, stereotyped, or negatively labeled. And, patients who have enrolled may be performative in their responses or withhold information for the same reasons.
When discussing sensitive health topics during CNS studies, participants can benefit from interacting with clinicians and researchers through a screen rather than face-to-face. With remote methods like telehealth and mobile chat features, patients who desire it can achieve a comfortable distance from the study team—close enough to complete check-ins and access healthcare support when needed, but removed enough to be discreet.
Similarly, the ability to respond to questionnaires, submit outcomes, and update health status remotely may encourage patients to be more honest and accurate in their reporting. With stressors—such as unfamiliar clinics and new clinicians—reduced or removed, patients are able to submit real-time, real-world data without having to confront situations that may bias that data.
Patient- and clinician-reported outcomes provide the basis for measuring most endpoints in CNS clinical trials. For example, in a clinical trial for depression, clinicians may leverage scales—such as the Montgomery-Åsberg Depression Rating Scale (MADRS)—to assess depressive symptom changes in patients. In the same study, participants may personally rate their symptoms, such as the severity of an anxiety attack or the quality of their sleep.
While these outcomes are important to capture, they are also prone to recall bias or skewed perceptions—particularly when there’s a long waiting period between experiencing and reporting a symptom. There is also the concern of variability within the expert rating process, which is subject to human error and can further impact data quality.
Achieving 100% objective reporting isn’t the goal of every CNS clinical trial. Some studies may require a combination of subjective and objective data, depending on chosen endpoints. But, wherever objective data is needed, leveraging technology to support humans can drive more accurate, consistent results.
Although not typically associated with CNS clinical development programs, sensors and wearables can serve as important tools for gathering continuous or point-in-time data. These data points—such as heart rate, step tracking, or sleep tracking—can be used to objectively measure symptom severity while also contextualizing patients’ own assessments of their symptoms.
More common to current CNS research are ePRO and eClinRo (electronic clinician-reported outcomes), which allow participants and clinicians to submit real-time data on behaviors and symptoms. For patients in particular, ePRO allows them to:
Meanwhile, an electronic clinical outcome assessment (eCOA) platform streamlines the expert review process, augmenting expert assessments by:
Whether they’re leveraged individually or together, all of these tools provide increased data accuracy to support stronger evidence and proof of efficacy.
In CNS clinical trials, the stakes can be extremely high. This research focuses on critical functions within the brain and nervous system. As a result, maintaining communication with patients and encouraging their engagement is essential—both for study outcomes and for ensuring patients’ safety. Participants who are out of compliance or who drop out entirely pose a major concern for study teams.
DCT and hybrid studies incorporate patient-centric processes, intuitive digital tools, and ongoing support to keep participants engaged throughout the study. These models use human-centric design to meet patients’ needs with flexibility while also ensuring their safety, including:
Well-designed DCTs don’t replace the human component of clinical research—they simply support humans in new ways at every stage of the trial.
More than 4,000 CNS clinical trials are expected to be underway by 2026, according to Evaluate Pharma. And, these trials require new approaches, according to researchers writing in the journal Therapies: “Central nervous system disorders remain the leading causes of mortality and morbidity worldwide, affecting more than 1 billion patients,” the authors indicate. “This therapeutic area suffers from high unmet medical needs and the search for innovative approaches to identify therapeutic strategies is urgent in the field.”
The potential for DCT models within CNS research can meet this urgency—with broad applications. By providing a multi-pronged solution, DCTs can address many of the challenges inherent in CNS trials, ultimately delivering stronger evidence and accelerating the speed to market for life-changing new treatments.
The challenges associated with conducting central nervous system clinical research all impact sponsors’ and study teams’ ability to gather stronger therapeutic evidence—but they also prime CNS studies for decentralization.
Common obstacles in CNS research include:
These challenges all impact sponsors’ and study teams’ ability to gather stronger therapeutic evidence—but they also prime CNS studies for decentralization.
Let’s dive into how decentralized clinical trials (DCTs), leveraging a modular approach, can address four key challenges in central nervous system research to reduce participant uncertainty and burden, increase participant compliance, and drive data quality.
Recruitment and retention in clinical studies for CNS diseases has become a major challenge for sponsors and the research teams who run these studies. As a result, CNS trials confront more frequent delays than those in other therapeutic areas, with associated increased costs.
According to research in Applied Clinical Trials, “[t]he reason for this is … smaller population[s] of patients compared to other indications,” as well as “the complicated and lengthy nature of these trials and the unique features of CNS diseases such as the mental dependency of patients suffering with neurodegenerative diseases.”
CNS disorders and health conditions can limit patients’ mobility, energy, and cognitive abilities, inhibiting—or even prohibiting—travel to and from clinical research sites and increasing their need for streamlined participant-facing tools and support.
In effect, many patients who stand to benefit the most from the development of a new CNS treatment or drug also confront the biggest barriers to study participation.
DCTs can bring CNS clinical trials directly to patients and their caregivers, addressing many of the barriers associated with patient recruitment and retention:
By reducing the participant burden from start to finish, DCT and hybrid clinical trial models broaden the pool of potential participants while also providing the support, tools and resources, and flexible processes patients need to supply quality data. This, in turn, supports better insights and, ultimately, stronger therapeutic evidence.
Much like reproductive and women’s health, many CNS conditions are still considered “taboo,” both on a cultural level and by patients themselves. Some potential participants may hesitate to enroll because of concerns about disclosing personal health information, being judged, stereotyped, or negatively labeled. And, patients who have enrolled may be performative in their responses or withhold information for the same reasons.
When discussing sensitive health topics during CNS studies, participants can benefit from interacting with clinicians and researchers through a screen rather than face-to-face. With remote methods like telehealth and mobile chat features, patients who desire it can achieve a comfortable distance from the study team—close enough to complete check-ins and access healthcare support when needed, but removed enough to be discreet.
Similarly, the ability to respond to questionnaires, submit outcomes, and update health status remotely may encourage patients to be more honest and accurate in their reporting. With stressors—such as unfamiliar clinics and new clinicians—reduced or removed, patients are able to submit real-time, real-world data without having to confront situations that may bias that data.
Patient- and clinician-reported outcomes provide the basis for measuring most endpoints in CNS clinical trials. For example, in a clinical trial for depression, clinicians may leverage scales—such as the Montgomery-Åsberg Depression Rating Scale (MADRS)—to assess depressive symptom changes in patients. In the same study, participants may personally rate their symptoms, such as the severity of an anxiety attack or the quality of their sleep.
While these outcomes are important to capture, they are also prone to recall bias or skewed perceptions—particularly when there’s a long waiting period between experiencing and reporting a symptom. There is also the concern of variability within the expert rating process, which is subject to human error and can further impact data quality.
Achieving 100% objective reporting isn’t the goal of every CNS clinical trial. Some studies may require a combination of subjective and objective data, depending on chosen endpoints. But, wherever objective data is needed, leveraging technology to support humans can drive more accurate, consistent results.
Although not typically associated with CNS clinical development programs, sensors and wearables can serve as important tools for gathering continuous or point-in-time data. These data points—such as heart rate, step tracking, or sleep tracking—can be used to objectively measure symptom severity while also contextualizing patients’ own assessments of their symptoms.
More common to current CNS research are ePRO and eClinRo (electronic clinician-reported outcomes), which allow participants and clinicians to submit real-time data on behaviors and symptoms. For patients in particular, ePRO allows them to:
Meanwhile, an electronic clinical outcome assessment (eCOA) platform streamlines the expert review process, augmenting expert assessments by:
Whether they’re leveraged individually or together, all of these tools provide increased data accuracy to support stronger evidence and proof of efficacy.
In CNS clinical trials, the stakes can be extremely high. This research focuses on critical functions within the brain and nervous system. As a result, maintaining communication with patients and encouraging their engagement is essential—both for study outcomes and for ensuring patients’ safety. Participants who are out of compliance or who drop out entirely pose a major concern for study teams.
DCT and hybrid studies incorporate patient-centric processes, intuitive digital tools, and ongoing support to keep participants engaged throughout the study. These models use human-centric design to meet patients’ needs with flexibility while also ensuring their safety, including:
Well-designed DCTs don’t replace the human component of clinical research—they simply support humans in new ways at every stage of the trial.
More than 4,000 CNS clinical trials are expected to be underway by 2026, according to Evaluate Pharma. And, these trials require new approaches, according to researchers writing in the journal Therapies: “Central nervous system disorders remain the leading causes of mortality and morbidity worldwide, affecting more than 1 billion patients,” the authors indicate. “This therapeutic area suffers from high unmet medical needs and the search for innovative approaches to identify therapeutic strategies is urgent in the field.”
The potential for DCT models within CNS research can meet this urgency—with broad applications. By providing a multi-pronged solution, DCTs can address many of the challenges inherent in CNS trials, ultimately delivering stronger evidence and accelerating the speed to market for life-changing new treatments.
Common obstacles in CNS research include:
These challenges all impact sponsors’ and study teams’ ability to gather stronger therapeutic evidence—but they also prime CNS studies for decentralization.
Let’s dive into how decentralized clinical trials (DCTs), leveraging a modular approach, can address four key challenges in central nervous system research to reduce participant uncertainty and burden, increase participant compliance, and drive data quality.
Recruitment and retention in clinical studies for CNS diseases has become a major challenge for sponsors and the research teams who run these studies. As a result, CNS trials confront more frequent delays than those in other therapeutic areas, with associated increased costs.
According to research in Applied Clinical Trials, “[t]he reason for this is … smaller population[s] of patients compared to other indications,” as well as “the complicated and lengthy nature of these trials and the unique features of CNS diseases such as the mental dependency of patients suffering with neurodegenerative diseases.”
CNS disorders and health conditions can limit patients’ mobility, energy, and cognitive abilities, inhibiting—or even prohibiting—travel to and from clinical research sites and increasing their need for streamlined participant-facing tools and support.
In effect, many patients who stand to benefit the most from the development of a new CNS treatment or drug also confront the biggest barriers to study participation.
DCTs can bring CNS clinical trials directly to patients and their caregivers, addressing many of the barriers associated with patient recruitment and retention:
By reducing the participant burden from start to finish, DCT and hybrid clinical trial models broaden the pool of potential participants while also providing the support, tools and resources, and flexible processes patients need to supply quality data. This, in turn, supports better insights and, ultimately, stronger therapeutic evidence.
Much like reproductive and women’s health, many CNS conditions are still considered “taboo,” both on a cultural level and by patients themselves. Some potential participants may hesitate to enroll because of concerns about disclosing personal health information, being judged, stereotyped, or negatively labeled. And, patients who have enrolled may be performative in their responses or withhold information for the same reasons.
When discussing sensitive health topics during CNS studies, participants can benefit from interacting with clinicians and researchers through a screen rather than face-to-face. With remote methods like telehealth and mobile chat features, patients who desire it can achieve a comfortable distance from the study team—close enough to complete check-ins and access healthcare support when needed, but removed enough to be discreet.
Similarly, the ability to respond to questionnaires, submit outcomes, and update health status remotely may encourage patients to be more honest and accurate in their reporting. With stressors—such as unfamiliar clinics and new clinicians—reduced or removed, patients are able to submit real-time, real-world data without having to confront situations that may bias that data.
Patient- and clinician-reported outcomes provide the basis for measuring most endpoints in CNS clinical trials. For example, in a clinical trial for depression, clinicians may leverage scales—such as the Montgomery-Åsberg Depression Rating Scale (MADRS)—to assess depressive symptom changes in patients. In the same study, participants may personally rate their symptoms, such as the severity of an anxiety attack or the quality of their sleep.
While these outcomes are important to capture, they are also prone to recall bias or skewed perceptions—particularly when there’s a long waiting period between experiencing and reporting a symptom. There is also the concern of variability within the expert rating process, which is subject to human error and can further impact data quality.
Achieving 100% objective reporting isn’t the goal of every CNS clinical trial. Some studies may require a combination of subjective and objective data, depending on chosen endpoints. But, wherever objective data is needed, leveraging technology to support humans can drive more accurate, consistent results.
Although not typically associated with CNS clinical development programs, sensors and wearables can serve as important tools for gathering continuous or point-in-time data. These data points—such as heart rate, step tracking, or sleep tracking—can be used to objectively measure symptom severity while also contextualizing patients’ own assessments of their symptoms.
More common to current CNS research are ePRO and eClinRo (electronic clinician-reported outcomes), which allow participants and clinicians to submit real-time data on behaviors and symptoms. For patients in particular, ePRO allows them to:
Meanwhile, an electronic clinical outcome assessment (eCOA) platform streamlines the expert review process, augmenting expert assessments by:
Whether they’re leveraged individually or together, all of these tools provide increased data accuracy to support stronger evidence and proof of efficacy.
In CNS clinical trials, the stakes can be extremely high. This research focuses on critical functions within the brain and nervous system. As a result, maintaining communication with patients and encouraging their engagement is essential—both for study outcomes and for ensuring patients’ safety. Participants who are out of compliance or who drop out entirely pose a major concern for study teams.
DCT and hybrid studies incorporate patient-centric processes, intuitive digital tools, and ongoing support to keep participants engaged throughout the study. These models use human-centric design to meet patients’ needs with flexibility while also ensuring their safety, including:
Well-designed DCTs don’t replace the human component of clinical research—they simply support humans in new ways at every stage of the trial.
More than 4,000 CNS clinical trials are expected to be underway by 2026, according to Evaluate Pharma. And, these trials require new approaches, according to researchers writing in the journal Therapies: “Central nervous system disorders remain the leading causes of mortality and morbidity worldwide, affecting more than 1 billion patients,” the authors indicate. “This therapeutic area suffers from high unmet medical needs and the search for innovative approaches to identify therapeutic strategies is urgent in the field.”
The potential for DCT models within CNS research can meet this urgency—with broad applications. By providing a multi-pronged solution, DCTs can address many of the challenges inherent in CNS trials, ultimately delivering stronger evidence and accelerating the speed to market for life-changing new treatments.
Common obstacles in CNS research include:
These challenges all impact sponsors’ and study teams’ ability to gather stronger therapeutic evidence—but they also prime CNS studies for decentralization.
Let’s dive into how decentralized clinical trials (DCTs), leveraging a modular approach, can address four key challenges in central nervous system research to reduce participant uncertainty and burden, increase participant compliance, and drive data quality.
Recruitment and retention in clinical studies for CNS diseases has become a major challenge for sponsors and the research teams who run these studies. As a result, CNS trials confront more frequent delays than those in other therapeutic areas, with associated increased costs.
According to research in Applied Clinical Trials, “[t]he reason for this is … smaller population[s] of patients compared to other indications,” as well as “the complicated and lengthy nature of these trials and the unique features of CNS diseases such as the mental dependency of patients suffering with neurodegenerative diseases.”
CNS disorders and health conditions can limit patients’ mobility, energy, and cognitive abilities, inhibiting—or even prohibiting—travel to and from clinical research sites and increasing their need for streamlined participant-facing tools and support.
In effect, many patients who stand to benefit the most from the development of a new CNS treatment or drug also confront the biggest barriers to study participation.
DCTs can bring CNS clinical trials directly to patients and their caregivers, addressing many of the barriers associated with patient recruitment and retention:
By reducing the participant burden from start to finish, DCT and hybrid clinical trial models broaden the pool of potential participants while also providing the support, tools and resources, and flexible processes patients need to supply quality data. This, in turn, supports better insights and, ultimately, stronger therapeutic evidence.
Much like reproductive and women’s health, many CNS conditions are still considered “taboo,” both on a cultural level and by patients themselves. Some potential participants may hesitate to enroll because of concerns about disclosing personal health information, being judged, stereotyped, or negatively labeled. And, patients who have enrolled may be performative in their responses or withhold information for the same reasons.
When discussing sensitive health topics during CNS studies, participants can benefit from interacting with clinicians and researchers through a screen rather than face-to-face. With remote methods like telehealth and mobile chat features, patients who desire it can achieve a comfortable distance from the study team—close enough to complete check-ins and access healthcare support when needed, but removed enough to be discreet.
Similarly, the ability to respond to questionnaires, submit outcomes, and update health status remotely may encourage patients to be more honest and accurate in their reporting. With stressors—such as unfamiliar clinics and new clinicians—reduced or removed, patients are able to submit real-time, real-world data without having to confront situations that may bias that data.
Patient- and clinician-reported outcomes provide the basis for measuring most endpoints in CNS clinical trials. For example, in a clinical trial for depression, clinicians may leverage scales—such as the Montgomery-Åsberg Depression Rating Scale (MADRS)—to assess depressive symptom changes in patients. In the same study, participants may personally rate their symptoms, such as the severity of an anxiety attack or the quality of their sleep.
While these outcomes are important to capture, they are also prone to recall bias or skewed perceptions—particularly when there’s a long waiting period between experiencing and reporting a symptom. There is also the concern of variability within the expert rating process, which is subject to human error and can further impact data quality.
Achieving 100% objective reporting isn’t the goal of every CNS clinical trial. Some studies may require a combination of subjective and objective data, depending on chosen endpoints. But, wherever objective data is needed, leveraging technology to support humans can drive more accurate, consistent results.
Although not typically associated with CNS clinical development programs, sensors and wearables can serve as important tools for gathering continuous or point-in-time data. These data points—such as heart rate, step tracking, or sleep tracking—can be used to objectively measure symptom severity while also contextualizing patients’ own assessments of their symptoms.
More common to current CNS research are ePRO and eClinRo (electronic clinician-reported outcomes), which allow participants and clinicians to submit real-time data on behaviors and symptoms. For patients in particular, ePRO allows them to:
Meanwhile, an electronic clinical outcome assessment (eCOA) platform streamlines the expert review process, augmenting expert assessments by:
Whether they’re leveraged individually or together, all of these tools provide increased data accuracy to support stronger evidence and proof of efficacy.
In CNS clinical trials, the stakes can be extremely high. This research focuses on critical functions within the brain and nervous system. As a result, maintaining communication with patients and encouraging their engagement is essential—both for study outcomes and for ensuring patients’ safety. Participants who are out of compliance or who drop out entirely pose a major concern for study teams.
DCT and hybrid studies incorporate patient-centric processes, intuitive digital tools, and ongoing support to keep participants engaged throughout the study. These models use human-centric design to meet patients’ needs with flexibility while also ensuring their safety, including:
Well-designed DCTs don’t replace the human component of clinical research—they simply support humans in new ways at every stage of the trial.
More than 4,000 CNS clinical trials are expected to be underway by 2026, according to Evaluate Pharma. And, these trials require new approaches, according to researchers writing in the journal Therapies: “Central nervous system disorders remain the leading causes of mortality and morbidity worldwide, affecting more than 1 billion patients,” the authors indicate. “This therapeutic area suffers from high unmet medical needs and the search for innovative approaches to identify therapeutic strategies is urgent in the field.”
The potential for DCT models within CNS research can meet this urgency—with broad applications. By providing a multi-pronged solution, DCTs can address many of the challenges inherent in CNS trials, ultimately delivering stronger evidence and accelerating the speed to market for life-changing new treatments.
The challenges associated with conducting central nervous system clinical research all impact sponsors’ and study teams’ ability to gather stronger therapeutic evidence—but they also prime CNS studies for decentralization.
Common obstacles in CNS research include:
These challenges all impact sponsors’ and study teams’ ability to gather stronger therapeutic evidence—but they also prime CNS studies for decentralization.
Let’s dive into how decentralized clinical trials (DCTs), leveraging a modular approach, can address four key challenges in central nervous system research to reduce participant uncertainty and burden, increase participant compliance, and drive data quality.
Recruitment and retention in clinical studies for CNS diseases has become a major challenge for sponsors and the research teams who run these studies. As a result, CNS trials confront more frequent delays than those in other therapeutic areas, with associated increased costs.
According to research in Applied Clinical Trials, “[t]he reason for this is … smaller population[s] of patients compared to other indications,” as well as “the complicated and lengthy nature of these trials and the unique features of CNS diseases such as the mental dependency of patients suffering with neurodegenerative diseases.”
CNS disorders and health conditions can limit patients’ mobility, energy, and cognitive abilities, inhibiting—or even prohibiting—travel to and from clinical research sites and increasing their need for streamlined participant-facing tools and support.
In effect, many patients who stand to benefit the most from the development of a new CNS treatment or drug also confront the biggest barriers to study participation.
DCTs can bring CNS clinical trials directly to patients and their caregivers, addressing many of the barriers associated with patient recruitment and retention:
By reducing the participant burden from start to finish, DCT and hybrid clinical trial models broaden the pool of potential participants while also providing the support, tools and resources, and flexible processes patients need to supply quality data. This, in turn, supports better insights and, ultimately, stronger therapeutic evidence.
Much like reproductive and women’s health, many CNS conditions are still considered “taboo,” both on a cultural level and by patients themselves. Some potential participants may hesitate to enroll because of concerns about disclosing personal health information, being judged, stereotyped, or negatively labeled. And, patients who have enrolled may be performative in their responses or withhold information for the same reasons.
When discussing sensitive health topics during CNS studies, participants can benefit from interacting with clinicians and researchers through a screen rather than face-to-face. With remote methods like telehealth and mobile chat features, patients who desire it can achieve a comfortable distance from the study team—close enough to complete check-ins and access healthcare support when needed, but removed enough to be discreet.
Similarly, the ability to respond to questionnaires, submit outcomes, and update health status remotely may encourage patients to be more honest and accurate in their reporting. With stressors—such as unfamiliar clinics and new clinicians—reduced or removed, patients are able to submit real-time, real-world data without having to confront situations that may bias that data.
Patient- and clinician-reported outcomes provide the basis for measuring most endpoints in CNS clinical trials. For example, in a clinical trial for depression, clinicians may leverage scales—such as the Montgomery-Åsberg Depression Rating Scale (MADRS)—to assess depressive symptom changes in patients. In the same study, participants may personally rate their symptoms, such as the severity of an anxiety attack or the quality of their sleep.
While these outcomes are important to capture, they are also prone to recall bias or skewed perceptions—particularly when there’s a long waiting period between experiencing and reporting a symptom. There is also the concern of variability within the expert rating process, which is subject to human error and can further impact data quality.
Achieving 100% objective reporting isn’t the goal of every CNS clinical trial. Some studies may require a combination of subjective and objective data, depending on chosen endpoints. But, wherever objective data is needed, leveraging technology to support humans can drive more accurate, consistent results.
Although not typically associated with CNS clinical development programs, sensors and wearables can serve as important tools for gathering continuous or point-in-time data. These data points—such as heart rate, step tracking, or sleep tracking—can be used to objectively measure symptom severity while also contextualizing patients’ own assessments of their symptoms.
More common to current CNS research are ePRO and eClinRo (electronic clinician-reported outcomes), which allow participants and clinicians to submit real-time data on behaviors and symptoms. For patients in particular, ePRO allows them to:
Meanwhile, an electronic clinical outcome assessment (eCOA) platform streamlines the expert review process, augmenting expert assessments by:
Whether they’re leveraged individually or together, all of these tools provide increased data accuracy to support stronger evidence and proof of efficacy.
In CNS clinical trials, the stakes can be extremely high. This research focuses on critical functions within the brain and nervous system. As a result, maintaining communication with patients and encouraging their engagement is essential—both for study outcomes and for ensuring patients’ safety. Participants who are out of compliance or who drop out entirely pose a major concern for study teams.
DCT and hybrid studies incorporate patient-centric processes, intuitive digital tools, and ongoing support to keep participants engaged throughout the study. These models use human-centric design to meet patients’ needs with flexibility while also ensuring their safety, including:
Well-designed DCTs don’t replace the human component of clinical research—they simply support humans in new ways at every stage of the trial.
More than 4,000 CNS clinical trials are expected to be underway by 2026, according to Evaluate Pharma. And, these trials require new approaches, according to researchers writing in the journal Therapies: “Central nervous system disorders remain the leading causes of mortality and morbidity worldwide, affecting more than 1 billion patients,” the authors indicate. “This therapeutic area suffers from high unmet medical needs and the search for innovative approaches to identify therapeutic strategies is urgent in the field.”
The potential for DCT models within CNS research can meet this urgency—with broad applications. By providing a multi-pronged solution, DCTs can address many of the challenges inherent in CNS trials, ultimately delivering stronger evidence and accelerating the speed to market for life-changing new treatments.
The challenges associated with conducting central nervous system clinical research all impact sponsors’ and study teams’ ability to gather stronger therapeutic evidence—but they also prime CNS studies for decentralization.
Common obstacles in CNS research include:
These challenges all impact sponsors’ and study teams’ ability to gather stronger therapeutic evidence—but they also prime CNS studies for decentralization.
Let’s dive into how decentralized clinical trials (DCTs), leveraging a modular approach, can address four key challenges in central nervous system research to reduce participant uncertainty and burden, increase participant compliance, and drive data quality.
Recruitment and retention in clinical studies for CNS diseases has become a major challenge for sponsors and the research teams who run these studies. As a result, CNS trials confront more frequent delays than those in other therapeutic areas, with associated increased costs.
According to research in Applied Clinical Trials, “[t]he reason for this is … smaller population[s] of patients compared to other indications,” as well as “the complicated and lengthy nature of these trials and the unique features of CNS diseases such as the mental dependency of patients suffering with neurodegenerative diseases.”
CNS disorders and health conditions can limit patients’ mobility, energy, and cognitive abilities, inhibiting—or even prohibiting—travel to and from clinical research sites and increasing their need for streamlined participant-facing tools and support.
In effect, many patients who stand to benefit the most from the development of a new CNS treatment or drug also confront the biggest barriers to study participation.
DCTs can bring CNS clinical trials directly to patients and their caregivers, addressing many of the barriers associated with patient recruitment and retention:
By reducing the participant burden from start to finish, DCT and hybrid clinical trial models broaden the pool of potential participants while also providing the support, tools and resources, and flexible processes patients need to supply quality data. This, in turn, supports better insights and, ultimately, stronger therapeutic evidence.
Much like reproductive and women’s health, many CNS conditions are still considered “taboo,” both on a cultural level and by patients themselves. Some potential participants may hesitate to enroll because of concerns about disclosing personal health information, being judged, stereotyped, or negatively labeled. And, patients who have enrolled may be performative in their responses or withhold information for the same reasons.
When discussing sensitive health topics during CNS studies, participants can benefit from interacting with clinicians and researchers through a screen rather than face-to-face. With remote methods like telehealth and mobile chat features, patients who desire it can achieve a comfortable distance from the study team—close enough to complete check-ins and access healthcare support when needed, but removed enough to be discreet.
Similarly, the ability to respond to questionnaires, submit outcomes, and update health status remotely may encourage patients to be more honest and accurate in their reporting. With stressors—such as unfamiliar clinics and new clinicians—reduced or removed, patients are able to submit real-time, real-world data without having to confront situations that may bias that data.
Patient- and clinician-reported outcomes provide the basis for measuring most endpoints in CNS clinical trials. For example, in a clinical trial for depression, clinicians may leverage scales—such as the Montgomery-Åsberg Depression Rating Scale (MADRS)—to assess depressive symptom changes in patients. In the same study, participants may personally rate their symptoms, such as the severity of an anxiety attack or the quality of their sleep.
While these outcomes are important to capture, they are also prone to recall bias or skewed perceptions—particularly when there’s a long waiting period between experiencing and reporting a symptom. There is also the concern of variability within the expert rating process, which is subject to human error and can further impact data quality.
Achieving 100% objective reporting isn’t the goal of every CNS clinical trial. Some studies may require a combination of subjective and objective data, depending on chosen endpoints. But, wherever objective data is needed, leveraging technology to support humans can drive more accurate, consistent results.
Although not typically associated with CNS clinical development programs, sensors and wearables can serve as important tools for gathering continuous or point-in-time data. These data points—such as heart rate, step tracking, or sleep tracking—can be used to objectively measure symptom severity while also contextualizing patients’ own assessments of their symptoms.
More common to current CNS research are ePRO and eClinRo (electronic clinician-reported outcomes), which allow participants and clinicians to submit real-time data on behaviors and symptoms. For patients in particular, ePRO allows them to:
Meanwhile, an electronic clinical outcome assessment (eCOA) platform streamlines the expert review process, augmenting expert assessments by:
Whether they’re leveraged individually or together, all of these tools provide increased data accuracy to support stronger evidence and proof of efficacy.
In CNS clinical trials, the stakes can be extremely high. This research focuses on critical functions within the brain and nervous system. As a result, maintaining communication with patients and encouraging their engagement is essential—both for study outcomes and for ensuring patients’ safety. Participants who are out of compliance or who drop out entirely pose a major concern for study teams.
DCT and hybrid studies incorporate patient-centric processes, intuitive digital tools, and ongoing support to keep participants engaged throughout the study. These models use human-centric design to meet patients’ needs with flexibility while also ensuring their safety, including:
Well-designed DCTs don’t replace the human component of clinical research—they simply support humans in new ways at every stage of the trial.
More than 4,000 CNS clinical trials are expected to be underway by 2026, according to Evaluate Pharma. And, these trials require new approaches, according to researchers writing in the journal Therapies: “Central nervous system disorders remain the leading causes of mortality and morbidity worldwide, affecting more than 1 billion patients,” the authors indicate. “This therapeutic area suffers from high unmet medical needs and the search for innovative approaches to identify therapeutic strategies is urgent in the field.”
The potential for DCT models within CNS research can meet this urgency—with broad applications. By providing a multi-pronged solution, DCTs can address many of the challenges inherent in CNS trials, ultimately delivering stronger evidence and accelerating the speed to market for life-changing new treatments.
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