Moving into 2022, decentralized models, propelled by breakthroughs in digital technology, will continue to reshape the industry, improving trial outcomes.
The promise of tech and digital solutions in clinical research has been evident for some time, recognized as a concrete solution to some of the industry's most challenging woes: trial inconvenience for patients, high trial costs for sponsors, and, in too many cases, suboptimal data quality.
Moving into 2022, decentralized models, propelled by breakthroughs in digital technology, will continue to reshape the industry's clinical trial trends, improving trial outcomes in four main ways:
At its core, trial decentralization is synonymous with convenience for patients. Going forward, this patient focus will extend to more customized approaches to clinical trials. Future trials will be designed to address the individual patient’s needs while reducing patient burden to a minimum.
Over the past year, protocols have begun to offer patients a choice of trial formats: telehealth versus at-home visits versus trips to the doctor, or a combination of these. The growing access to virtual study coordinators will expand patient options, allowing them to communicate whenever necessary or desired.
Patients will begin to have greater access to their data via their app or patient dashboards, offering visibility into the state of their health and wellness and the ability to monitor outcomes even after their specific trial is completed.
More complex to execute but potentially most groundbreaking will be the trend towards adaptive clinical trials that evolve according to patient response. For example: “[I]f a drug is not working, it would be pulled from the trial, and another treatment can take its place.” Aaron Miller, a medical oncologist at the UC San Diego Health System, continues, "And if a drug is working, it can move more quickly through the trial and to the FDA for potential approval."
The gravitation towards more patient-centric studies also has significant implications for the Patient Care Continuum. As digital solutions continue to bridge the gap between research and healthcare, decentralized studies will be leveraged as viable care options. For patients who are interested in, recommended for, or might require novel treatments, clinical trials will serve increasingly as supplementary—even sole—forms of care. (Read more about our decentralized clinical trials or our dedicated blog post on patient centricity in clinical trials)
Decentralized models offer sites new virtual components that simplify some of their more arduous responsibilities, saving both patient and staff time. Targeted digital recruitment for clinical trials will continue to grow, replacing the less efficient classic advertising methods. Digital prescreening and electronic consents will further reduce site staff burden. Simple site visits will increasingly give way to secure video calls. This will allow on-site clinical site teams to avoid paperwork and focus their time and energy on visiting patients.
A derivative benefit of remote patient participation is that it will allow for more flexible working situations for site employees, which, according to a survey conducted by Advarra, "is in line with how [site staff] would like to work moving forward." Site staff will, of course, need to spend more time training to adapt to new technologies and remote working methods, reinforcing the need to simplify the number and complexity of the platforms they interact with.
The industry will place greater emphasis on addressing the problem of subjectivity in electronic patient-reported outcomes (ePRO). The shift to at-home data collection will drive the development of digital research instruments that can be quickly and accurately administered from home. The result of these initiatives will be an ever-expanding library of instruments that enable the collection of continuous, objective, and often unstructured data.
For example, rather than simply filling in diaries or surveys, mobile devices equipped with intuitive apps will allow patients to take pictures of certain symptoms—in real time—and upload this data to an interface for expert assessment. The same will hold for other forms of media—including audio and video capture—which will be auto-detected or recorded and submitted by patients with just a few taps on a screen.
These streamlined approaches will reduce patient burden and subjectivity while increasing outcome accuracy. We will also see greater use of algorithms—trained using annotations/clinical notes—to augment expert raters. This combination of new technologies and analysis methods will drive towards novel outcomes that progress the way we measure trial endpoints.
Health researchers have spent the last several years lauding the potential of real-world data (RWD) to "revolutionize every stage of clinical research, from trial design to outcomes measurement." However, personal information and privacy protections, regulatory constraints, and siloed data structures have made RWD relatively inaccessible for use in clinical trials.
2021 witnessed slow but steady progress in this area: The accelerated use of machine learning tools to navigate and aggregate data from different silos facilitated the search and analysis of claims and other data to address unanswered questions around COVID impacts. The growing ability of AI to probe patient data—including medical histories, labs, scans, clinician notes, and other documentation—points to the growing role that RWD will play in health innovation moving forward.
In 2022, we will see more study designs using RWD to refine cohort definition and disease states. RWD will help recruit rare disease populations and create synthetic trial control arms. There will be a continued need for rigorous adherence to methodology and transparency to minimize bias and ensure data quality, but the benefits will outweigh both the complexity and the costs.
As the COVID-19 pandemic stretches into 2022, patients and researchers alike are adapting to a clinical trial market that has been substantially modified. While the landscape is still in flux, we expect to see an acceleration of the fundamental technological and behavioral shifts that are reshaping the industry to benefit patients, sponsors, and healthcare professionals alike.
The promise of tech and digital solutions in clinical research has been evident for some time, recognized as a concrete solution to some of the industry's most challenging woes: trial inconvenience for patients, high trial costs for sponsors, and, in too many cases, suboptimal data quality.
Moving into 2022, decentralized models, propelled by breakthroughs in digital technology, will continue to reshape the industry's clinical trial trends, improving trial outcomes in four main ways:
At its core, trial decentralization is synonymous with convenience for patients. Going forward, this patient focus will extend to more customized approaches to clinical trials. Future trials will be designed to address the individual patient’s needs while reducing patient burden to a minimum.
Over the past year, protocols have begun to offer patients a choice of trial formats: telehealth versus at-home visits versus trips to the doctor, or a combination of these. The growing access to virtual study coordinators will expand patient options, allowing them to communicate whenever necessary or desired.
Patients will begin to have greater access to their data via their app or patient dashboards, offering visibility into the state of their health and wellness and the ability to monitor outcomes even after their specific trial is completed.
More complex to execute but potentially most groundbreaking will be the trend towards adaptive clinical trials that evolve according to patient response. For example: “[I]f a drug is not working, it would be pulled from the trial, and another treatment can take its place.” Aaron Miller, a medical oncologist at the UC San Diego Health System, continues, "And if a drug is working, it can move more quickly through the trial and to the FDA for potential approval."
The gravitation towards more patient-centric studies also has significant implications for the Patient Care Continuum. As digital solutions continue to bridge the gap between research and healthcare, decentralized studies will be leveraged as viable care options. For patients who are interested in, recommended for, or might require novel treatments, clinical trials will serve increasingly as supplementary—even sole—forms of care. (Read more about our decentralized clinical trials or our dedicated blog post on patient centricity in clinical trials)
Decentralized models offer sites new virtual components that simplify some of their more arduous responsibilities, saving both patient and staff time. Targeted digital recruitment for clinical trials will continue to grow, replacing the less efficient classic advertising methods. Digital prescreening and electronic consents will further reduce site staff burden. Simple site visits will increasingly give way to secure video calls. This will allow on-site clinical site teams to avoid paperwork and focus their time and energy on visiting patients.
A derivative benefit of remote patient participation is that it will allow for more flexible working situations for site employees, which, according to a survey conducted by Advarra, "is in line with how [site staff] would like to work moving forward." Site staff will, of course, need to spend more time training to adapt to new technologies and remote working methods, reinforcing the need to simplify the number and complexity of the platforms they interact with.
The industry will place greater emphasis on addressing the problem of subjectivity in electronic patient-reported outcomes (ePRO). The shift to at-home data collection will drive the development of digital research instruments that can be quickly and accurately administered from home. The result of these initiatives will be an ever-expanding library of instruments that enable the collection of continuous, objective, and often unstructured data.
For example, rather than simply filling in diaries or surveys, mobile devices equipped with intuitive apps will allow patients to take pictures of certain symptoms—in real time—and upload this data to an interface for expert assessment. The same will hold for other forms of media—including audio and video capture—which will be auto-detected or recorded and submitted by patients with just a few taps on a screen.
These streamlined approaches will reduce patient burden and subjectivity while increasing outcome accuracy. We will also see greater use of algorithms—trained using annotations/clinical notes—to augment expert raters. This combination of new technologies and analysis methods will drive towards novel outcomes that progress the way we measure trial endpoints.
Health researchers have spent the last several years lauding the potential of real-world data (RWD) to "revolutionize every stage of clinical research, from trial design to outcomes measurement." However, personal information and privacy protections, regulatory constraints, and siloed data structures have made RWD relatively inaccessible for use in clinical trials.
2021 witnessed slow but steady progress in this area: The accelerated use of machine learning tools to navigate and aggregate data from different silos facilitated the search and analysis of claims and other data to address unanswered questions around COVID impacts. The growing ability of AI to probe patient data—including medical histories, labs, scans, clinician notes, and other documentation—points to the growing role that RWD will play in health innovation moving forward.
In 2022, we will see more study designs using RWD to refine cohort definition and disease states. RWD will help recruit rare disease populations and create synthetic trial control arms. There will be a continued need for rigorous adherence to methodology and transparency to minimize bias and ensure data quality, but the benefits will outweigh both the complexity and the costs.
As the COVID-19 pandemic stretches into 2022, patients and researchers alike are adapting to a clinical trial market that has been substantially modified. While the landscape is still in flux, we expect to see an acceleration of the fundamental technological and behavioral shifts that are reshaping the industry to benefit patients, sponsors, and healthcare professionals alike.
Moving into 2022, decentralized models, propelled by breakthroughs in digital technology, will continue to reshape the industry, improving trial outcomes.
The promise of tech and digital solutions in clinical research has been evident for some time, recognized as a concrete solution to some of the industry's most challenging woes: trial inconvenience for patients, high trial costs for sponsors, and, in too many cases, suboptimal data quality.
Moving into 2022, decentralized models, propelled by breakthroughs in digital technology, will continue to reshape the industry's clinical trial trends, improving trial outcomes in four main ways:
At its core, trial decentralization is synonymous with convenience for patients. Going forward, this patient focus will extend to more customized approaches to clinical trials. Future trials will be designed to address the individual patient’s needs while reducing patient burden to a minimum.
Over the past year, protocols have begun to offer patients a choice of trial formats: telehealth versus at-home visits versus trips to the doctor, or a combination of these. The growing access to virtual study coordinators will expand patient options, allowing them to communicate whenever necessary or desired.
Patients will begin to have greater access to their data via their app or patient dashboards, offering visibility into the state of their health and wellness and the ability to monitor outcomes even after their specific trial is completed.
More complex to execute but potentially most groundbreaking will be the trend towards adaptive clinical trials that evolve according to patient response. For example: “[I]f a drug is not working, it would be pulled from the trial, and another treatment can take its place.” Aaron Miller, a medical oncologist at the UC San Diego Health System, continues, "And if a drug is working, it can move more quickly through the trial and to the FDA for potential approval."
The gravitation towards more patient-centric studies also has significant implications for the Patient Care Continuum. As digital solutions continue to bridge the gap between research and healthcare, decentralized studies will be leveraged as viable care options. For patients who are interested in, recommended for, or might require novel treatments, clinical trials will serve increasingly as supplementary—even sole—forms of care. (Read more about our decentralized clinical trials or our dedicated blog post on patient centricity in clinical trials)
Decentralized models offer sites new virtual components that simplify some of their more arduous responsibilities, saving both patient and staff time. Targeted digital recruitment for clinical trials will continue to grow, replacing the less efficient classic advertising methods. Digital prescreening and electronic consents will further reduce site staff burden. Simple site visits will increasingly give way to secure video calls. This will allow on-site clinical site teams to avoid paperwork and focus their time and energy on visiting patients.
A derivative benefit of remote patient participation is that it will allow for more flexible working situations for site employees, which, according to a survey conducted by Advarra, "is in line with how [site staff] would like to work moving forward." Site staff will, of course, need to spend more time training to adapt to new technologies and remote working methods, reinforcing the need to simplify the number and complexity of the platforms they interact with.
The industry will place greater emphasis on addressing the problem of subjectivity in electronic patient-reported outcomes (ePRO). The shift to at-home data collection will drive the development of digital research instruments that can be quickly and accurately administered from home. The result of these initiatives will be an ever-expanding library of instruments that enable the collection of continuous, objective, and often unstructured data.
For example, rather than simply filling in diaries or surveys, mobile devices equipped with intuitive apps will allow patients to take pictures of certain symptoms—in real time—and upload this data to an interface for expert assessment. The same will hold for other forms of media—including audio and video capture—which will be auto-detected or recorded and submitted by patients with just a few taps on a screen.
These streamlined approaches will reduce patient burden and subjectivity while increasing outcome accuracy. We will also see greater use of algorithms—trained using annotations/clinical notes—to augment expert raters. This combination of new technologies and analysis methods will drive towards novel outcomes that progress the way we measure trial endpoints.
Health researchers have spent the last several years lauding the potential of real-world data (RWD) to "revolutionize every stage of clinical research, from trial design to outcomes measurement." However, personal information and privacy protections, regulatory constraints, and siloed data structures have made RWD relatively inaccessible for use in clinical trials.
2021 witnessed slow but steady progress in this area: The accelerated use of machine learning tools to navigate and aggregate data from different silos facilitated the search and analysis of claims and other data to address unanswered questions around COVID impacts. The growing ability of AI to probe patient data—including medical histories, labs, scans, clinician notes, and other documentation—points to the growing role that RWD will play in health innovation moving forward.
In 2022, we will see more study designs using RWD to refine cohort definition and disease states. RWD will help recruit rare disease populations and create synthetic trial control arms. There will be a continued need for rigorous adherence to methodology and transparency to minimize bias and ensure data quality, but the benefits will outweigh both the complexity and the costs.
As the COVID-19 pandemic stretches into 2022, patients and researchers alike are adapting to a clinical trial market that has been substantially modified. While the landscape is still in flux, we expect to see an acceleration of the fundamental technological and behavioral shifts that are reshaping the industry to benefit patients, sponsors, and healthcare professionals alike.
The promise of tech and digital solutions in clinical research has been evident for some time, recognized as a concrete solution to some of the industry's most challenging woes: trial inconvenience for patients, high trial costs for sponsors, and, in too many cases, suboptimal data quality.
Moving into 2022, decentralized models, propelled by breakthroughs in digital technology, will continue to reshape the industry's clinical trial trends, improving trial outcomes in four main ways:
At its core, trial decentralization is synonymous with convenience for patients. Going forward, this patient focus will extend to more customized approaches to clinical trials. Future trials will be designed to address the individual patient’s needs while reducing patient burden to a minimum.
Over the past year, protocols have begun to offer patients a choice of trial formats: telehealth versus at-home visits versus trips to the doctor, or a combination of these. The growing access to virtual study coordinators will expand patient options, allowing them to communicate whenever necessary or desired.
Patients will begin to have greater access to their data via their app or patient dashboards, offering visibility into the state of their health and wellness and the ability to monitor outcomes even after their specific trial is completed.
More complex to execute but potentially most groundbreaking will be the trend towards adaptive clinical trials that evolve according to patient response. For example: “[I]f a drug is not working, it would be pulled from the trial, and another treatment can take its place.” Aaron Miller, a medical oncologist at the UC San Diego Health System, continues, "And if a drug is working, it can move more quickly through the trial and to the FDA for potential approval."
The gravitation towards more patient-centric studies also has significant implications for the Patient Care Continuum. As digital solutions continue to bridge the gap between research and healthcare, decentralized studies will be leveraged as viable care options. For patients who are interested in, recommended for, or might require novel treatments, clinical trials will serve increasingly as supplementary—even sole—forms of care. (Read more about our decentralized clinical trials or our dedicated blog post on patient centricity in clinical trials)
Decentralized models offer sites new virtual components that simplify some of their more arduous responsibilities, saving both patient and staff time. Targeted digital recruitment for clinical trials will continue to grow, replacing the less efficient classic advertising methods. Digital prescreening and electronic consents will further reduce site staff burden. Simple site visits will increasingly give way to secure video calls. This will allow on-site clinical site teams to avoid paperwork and focus their time and energy on visiting patients.
A derivative benefit of remote patient participation is that it will allow for more flexible working situations for site employees, which, according to a survey conducted by Advarra, "is in line with how [site staff] would like to work moving forward." Site staff will, of course, need to spend more time training to adapt to new technologies and remote working methods, reinforcing the need to simplify the number and complexity of the platforms they interact with.
The industry will place greater emphasis on addressing the problem of subjectivity in electronic patient-reported outcomes (ePRO). The shift to at-home data collection will drive the development of digital research instruments that can be quickly and accurately administered from home. The result of these initiatives will be an ever-expanding library of instruments that enable the collection of continuous, objective, and often unstructured data.
For example, rather than simply filling in diaries or surveys, mobile devices equipped with intuitive apps will allow patients to take pictures of certain symptoms—in real time—and upload this data to an interface for expert assessment. The same will hold for other forms of media—including audio and video capture—which will be auto-detected or recorded and submitted by patients with just a few taps on a screen.
These streamlined approaches will reduce patient burden and subjectivity while increasing outcome accuracy. We will also see greater use of algorithms—trained using annotations/clinical notes—to augment expert raters. This combination of new technologies and analysis methods will drive towards novel outcomes that progress the way we measure trial endpoints.
Health researchers have spent the last several years lauding the potential of real-world data (RWD) to "revolutionize every stage of clinical research, from trial design to outcomes measurement." However, personal information and privacy protections, regulatory constraints, and siloed data structures have made RWD relatively inaccessible for use in clinical trials.
2021 witnessed slow but steady progress in this area: The accelerated use of machine learning tools to navigate and aggregate data from different silos facilitated the search and analysis of claims and other data to address unanswered questions around COVID impacts. The growing ability of AI to probe patient data—including medical histories, labs, scans, clinician notes, and other documentation—points to the growing role that RWD will play in health innovation moving forward.
In 2022, we will see more study designs using RWD to refine cohort definition and disease states. RWD will help recruit rare disease populations and create synthetic trial control arms. There will be a continued need for rigorous adherence to methodology and transparency to minimize bias and ensure data quality, but the benefits will outweigh both the complexity and the costs.
As the COVID-19 pandemic stretches into 2022, patients and researchers alike are adapting to a clinical trial market that has been substantially modified. While the landscape is still in flux, we expect to see an acceleration of the fundamental technological and behavioral shifts that are reshaping the industry to benefit patients, sponsors, and healthcare professionals alike.
The promise of tech and digital solutions in clinical research has been evident for some time, recognized as a concrete solution to some of the industry's most challenging woes: trial inconvenience for patients, high trial costs for sponsors, and, in too many cases, suboptimal data quality.
Moving into 2022, decentralized models, propelled by breakthroughs in digital technology, will continue to reshape the industry's clinical trial trends, improving trial outcomes in four main ways:
At its core, trial decentralization is synonymous with convenience for patients. Going forward, this patient focus will extend to more customized approaches to clinical trials. Future trials will be designed to address the individual patient’s needs while reducing patient burden to a minimum.
Over the past year, protocols have begun to offer patients a choice of trial formats: telehealth versus at-home visits versus trips to the doctor, or a combination of these. The growing access to virtual study coordinators will expand patient options, allowing them to communicate whenever necessary or desired.
Patients will begin to have greater access to their data via their app or patient dashboards, offering visibility into the state of their health and wellness and the ability to monitor outcomes even after their specific trial is completed.
More complex to execute but potentially most groundbreaking will be the trend towards adaptive clinical trials that evolve according to patient response. For example: “[I]f a drug is not working, it would be pulled from the trial, and another treatment can take its place.” Aaron Miller, a medical oncologist at the UC San Diego Health System, continues, "And if a drug is working, it can move more quickly through the trial and to the FDA for potential approval."
The gravitation towards more patient-centric studies also has significant implications for the Patient Care Continuum. As digital solutions continue to bridge the gap between research and healthcare, decentralized studies will be leveraged as viable care options. For patients who are interested in, recommended for, or might require novel treatments, clinical trials will serve increasingly as supplementary—even sole—forms of care. (Read more about our decentralized clinical trials or our dedicated blog post on patient centricity in clinical trials)
Decentralized models offer sites new virtual components that simplify some of their more arduous responsibilities, saving both patient and staff time. Targeted digital recruitment for clinical trials will continue to grow, replacing the less efficient classic advertising methods. Digital prescreening and electronic consents will further reduce site staff burden. Simple site visits will increasingly give way to secure video calls. This will allow on-site clinical site teams to avoid paperwork and focus their time and energy on visiting patients.
A derivative benefit of remote patient participation is that it will allow for more flexible working situations for site employees, which, according to a survey conducted by Advarra, "is in line with how [site staff] would like to work moving forward." Site staff will, of course, need to spend more time training to adapt to new technologies and remote working methods, reinforcing the need to simplify the number and complexity of the platforms they interact with.
The industry will place greater emphasis on addressing the problem of subjectivity in electronic patient-reported outcomes (ePRO). The shift to at-home data collection will drive the development of digital research instruments that can be quickly and accurately administered from home. The result of these initiatives will be an ever-expanding library of instruments that enable the collection of continuous, objective, and often unstructured data.
For example, rather than simply filling in diaries or surveys, mobile devices equipped with intuitive apps will allow patients to take pictures of certain symptoms—in real time—and upload this data to an interface for expert assessment. The same will hold for other forms of media—including audio and video capture—which will be auto-detected or recorded and submitted by patients with just a few taps on a screen.
These streamlined approaches will reduce patient burden and subjectivity while increasing outcome accuracy. We will also see greater use of algorithms—trained using annotations/clinical notes—to augment expert raters. This combination of new technologies and analysis methods will drive towards novel outcomes that progress the way we measure trial endpoints.
Health researchers have spent the last several years lauding the potential of real-world data (RWD) to "revolutionize every stage of clinical research, from trial design to outcomes measurement." However, personal information and privacy protections, regulatory constraints, and siloed data structures have made RWD relatively inaccessible for use in clinical trials.
2021 witnessed slow but steady progress in this area: The accelerated use of machine learning tools to navigate and aggregate data from different silos facilitated the search and analysis of claims and other data to address unanswered questions around COVID impacts. The growing ability of AI to probe patient data—including medical histories, labs, scans, clinician notes, and other documentation—points to the growing role that RWD will play in health innovation moving forward.
In 2022, we will see more study designs using RWD to refine cohort definition and disease states. RWD will help recruit rare disease populations and create synthetic trial control arms. There will be a continued need for rigorous adherence to methodology and transparency to minimize bias and ensure data quality, but the benefits will outweigh both the complexity and the costs.
As the COVID-19 pandemic stretches into 2022, patients and researchers alike are adapting to a clinical trial market that has been substantially modified. While the landscape is still in flux, we expect to see an acceleration of the fundamental technological and behavioral shifts that are reshaping the industry to benefit patients, sponsors, and healthcare professionals alike.
Moving into 2022, decentralized models, propelled by breakthroughs in digital technology, will continue to reshape the industry, improving trial outcomes.
The promise of tech and digital solutions in clinical research has been evident for some time, recognized as a concrete solution to some of the industry's most challenging woes: trial inconvenience for patients, high trial costs for sponsors, and, in too many cases, suboptimal data quality.
Moving into 2022, decentralized models, propelled by breakthroughs in digital technology, will continue to reshape the industry's clinical trial trends, improving trial outcomes in four main ways:
At its core, trial decentralization is synonymous with convenience for patients. Going forward, this patient focus will extend to more customized approaches to clinical trials. Future trials will be designed to address the individual patient’s needs while reducing patient burden to a minimum.
Over the past year, protocols have begun to offer patients a choice of trial formats: telehealth versus at-home visits versus trips to the doctor, or a combination of these. The growing access to virtual study coordinators will expand patient options, allowing them to communicate whenever necessary or desired.
Patients will begin to have greater access to their data via their app or patient dashboards, offering visibility into the state of their health and wellness and the ability to monitor outcomes even after their specific trial is completed.
More complex to execute but potentially most groundbreaking will be the trend towards adaptive clinical trials that evolve according to patient response. For example: “[I]f a drug is not working, it would be pulled from the trial, and another treatment can take its place.” Aaron Miller, a medical oncologist at the UC San Diego Health System, continues, "And if a drug is working, it can move more quickly through the trial and to the FDA for potential approval."
The gravitation towards more patient-centric studies also has significant implications for the Patient Care Continuum. As digital solutions continue to bridge the gap between research and healthcare, decentralized studies will be leveraged as viable care options. For patients who are interested in, recommended for, or might require novel treatments, clinical trials will serve increasingly as supplementary—even sole—forms of care. (Read more about our decentralized clinical trials or our dedicated blog post on patient centricity in clinical trials)
Decentralized models offer sites new virtual components that simplify some of their more arduous responsibilities, saving both patient and staff time. Targeted digital recruitment for clinical trials will continue to grow, replacing the less efficient classic advertising methods. Digital prescreening and electronic consents will further reduce site staff burden. Simple site visits will increasingly give way to secure video calls. This will allow on-site clinical site teams to avoid paperwork and focus their time and energy on visiting patients.
A derivative benefit of remote patient participation is that it will allow for more flexible working situations for site employees, which, according to a survey conducted by Advarra, "is in line with how [site staff] would like to work moving forward." Site staff will, of course, need to spend more time training to adapt to new technologies and remote working methods, reinforcing the need to simplify the number and complexity of the platforms they interact with.
The industry will place greater emphasis on addressing the problem of subjectivity in electronic patient-reported outcomes (ePRO). The shift to at-home data collection will drive the development of digital research instruments that can be quickly and accurately administered from home. The result of these initiatives will be an ever-expanding library of instruments that enable the collection of continuous, objective, and often unstructured data.
For example, rather than simply filling in diaries or surveys, mobile devices equipped with intuitive apps will allow patients to take pictures of certain symptoms—in real time—and upload this data to an interface for expert assessment. The same will hold for other forms of media—including audio and video capture—which will be auto-detected or recorded and submitted by patients with just a few taps on a screen.
These streamlined approaches will reduce patient burden and subjectivity while increasing outcome accuracy. We will also see greater use of algorithms—trained using annotations/clinical notes—to augment expert raters. This combination of new technologies and analysis methods will drive towards novel outcomes that progress the way we measure trial endpoints.
Health researchers have spent the last several years lauding the potential of real-world data (RWD) to "revolutionize every stage of clinical research, from trial design to outcomes measurement." However, personal information and privacy protections, regulatory constraints, and siloed data structures have made RWD relatively inaccessible for use in clinical trials.
2021 witnessed slow but steady progress in this area: The accelerated use of machine learning tools to navigate and aggregate data from different silos facilitated the search and analysis of claims and other data to address unanswered questions around COVID impacts. The growing ability of AI to probe patient data—including medical histories, labs, scans, clinician notes, and other documentation—points to the growing role that RWD will play in health innovation moving forward.
In 2022, we will see more study designs using RWD to refine cohort definition and disease states. RWD will help recruit rare disease populations and create synthetic trial control arms. There will be a continued need for rigorous adherence to methodology and transparency to minimize bias and ensure data quality, but the benefits will outweigh both the complexity and the costs.
As the COVID-19 pandemic stretches into 2022, patients and researchers alike are adapting to a clinical trial market that has been substantially modified. While the landscape is still in flux, we expect to see an acceleration of the fundamental technological and behavioral shifts that are reshaping the industry to benefit patients, sponsors, and healthcare professionals alike.
Moving into 2022, decentralized models, propelled by breakthroughs in digital technology, will continue to reshape the industry, improving trial outcomes.
The promise of tech and digital solutions in clinical research has been evident for some time, recognized as a concrete solution to some of the industry's most challenging woes: trial inconvenience for patients, high trial costs for sponsors, and, in too many cases, suboptimal data quality.
Moving into 2022, decentralized models, propelled by breakthroughs in digital technology, will continue to reshape the industry's clinical trial trends, improving trial outcomes in four main ways:
At its core, trial decentralization is synonymous with convenience for patients. Going forward, this patient focus will extend to more customized approaches to clinical trials. Future trials will be designed to address the individual patient’s needs while reducing patient burden to a minimum.
Over the past year, protocols have begun to offer patients a choice of trial formats: telehealth versus at-home visits versus trips to the doctor, or a combination of these. The growing access to virtual study coordinators will expand patient options, allowing them to communicate whenever necessary or desired.
Patients will begin to have greater access to their data via their app or patient dashboards, offering visibility into the state of their health and wellness and the ability to monitor outcomes even after their specific trial is completed.
More complex to execute but potentially most groundbreaking will be the trend towards adaptive clinical trials that evolve according to patient response. For example: “[I]f a drug is not working, it would be pulled from the trial, and another treatment can take its place.” Aaron Miller, a medical oncologist at the UC San Diego Health System, continues, "And if a drug is working, it can move more quickly through the trial and to the FDA for potential approval."
The gravitation towards more patient-centric studies also has significant implications for the Patient Care Continuum. As digital solutions continue to bridge the gap between research and healthcare, decentralized studies will be leveraged as viable care options. For patients who are interested in, recommended for, or might require novel treatments, clinical trials will serve increasingly as supplementary—even sole—forms of care. (Read more about our decentralized clinical trials or our dedicated blog post on patient centricity in clinical trials)
Decentralized models offer sites new virtual components that simplify some of their more arduous responsibilities, saving both patient and staff time. Targeted digital recruitment for clinical trials will continue to grow, replacing the less efficient classic advertising methods. Digital prescreening and electronic consents will further reduce site staff burden. Simple site visits will increasingly give way to secure video calls. This will allow on-site clinical site teams to avoid paperwork and focus their time and energy on visiting patients.
A derivative benefit of remote patient participation is that it will allow for more flexible working situations for site employees, which, according to a survey conducted by Advarra, "is in line with how [site staff] would like to work moving forward." Site staff will, of course, need to spend more time training to adapt to new technologies and remote working methods, reinforcing the need to simplify the number and complexity of the platforms they interact with.
The industry will place greater emphasis on addressing the problem of subjectivity in electronic patient-reported outcomes (ePRO). The shift to at-home data collection will drive the development of digital research instruments that can be quickly and accurately administered from home. The result of these initiatives will be an ever-expanding library of instruments that enable the collection of continuous, objective, and often unstructured data.
For example, rather than simply filling in diaries or surveys, mobile devices equipped with intuitive apps will allow patients to take pictures of certain symptoms—in real time—and upload this data to an interface for expert assessment. The same will hold for other forms of media—including audio and video capture—which will be auto-detected or recorded and submitted by patients with just a few taps on a screen.
These streamlined approaches will reduce patient burden and subjectivity while increasing outcome accuracy. We will also see greater use of algorithms—trained using annotations/clinical notes—to augment expert raters. This combination of new technologies and analysis methods will drive towards novel outcomes that progress the way we measure trial endpoints.
Health researchers have spent the last several years lauding the potential of real-world data (RWD) to "revolutionize every stage of clinical research, from trial design to outcomes measurement." However, personal information and privacy protections, regulatory constraints, and siloed data structures have made RWD relatively inaccessible for use in clinical trials.
2021 witnessed slow but steady progress in this area: The accelerated use of machine learning tools to navigate and aggregate data from different silos facilitated the search and analysis of claims and other data to address unanswered questions around COVID impacts. The growing ability of AI to probe patient data—including medical histories, labs, scans, clinician notes, and other documentation—points to the growing role that RWD will play in health innovation moving forward.
In 2022, we will see more study designs using RWD to refine cohort definition and disease states. RWD will help recruit rare disease populations and create synthetic trial control arms. There will be a continued need for rigorous adherence to methodology and transparency to minimize bias and ensure data quality, but the benefits will outweigh both the complexity and the costs.
As the COVID-19 pandemic stretches into 2022, patients and researchers alike are adapting to a clinical trial market that has been substantially modified. While the landscape is still in flux, we expect to see an acceleration of the fundamental technological and behavioral shifts that are reshaping the industry to benefit patients, sponsors, and healthcare professionals alike.
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