2020
DOI: 10.1038/s41582-020-0362-2
|View full text |Cite
|
Sign up to set email alerts
|

Discovery and validation of biomarkers to aid the development of safe and effective pain therapeutics: challenges and opportunities

Abstract: Pain medication plays an important role in the treatment of acute and chronic pain conditions, but some drugs, opioids in particular, have been overprescribed or prescribed without adequate safeguards, leading to an alarming rise in medication-related overdose deaths. The NIH Helping to End Addiction Long-term (HEAL) Initiative is a trans-agency effort to provide scientific solutions to stem the opioid crisis. One component of the initiative is to support biomarker discovery and rigorous validation in collabor… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

2
238
0
1

Year Published

2020
2020
2024
2024

Publication Types

Select...
6
2

Relationship

2
6

Authors

Journals

citations
Cited by 292 publications
(267 citation statements)
references
References 233 publications
2
238
0
1
Order By: Relevance
“…Even comparing non-painful and painful stimuli shows marked differences whereby the former resembles a network formation akin to resting-state (Zheng et al, 2020). The cluster of edges identified in the present study captures variance associated with additive genetics supporting the search for a genetically informed neural pain signature (Davis et al, 2020). Future studies should compare resting-state and pain-evoked functional connectivity and estimate the extent of their shared genetics and the neural targets of their shared and non-shared genes.…”
Section: Discussionsupporting
confidence: 69%
See 2 more Smart Citations
“…Even comparing non-painful and painful stimuli shows marked differences whereby the former resembles a network formation akin to resting-state (Zheng et al, 2020). The cluster of edges identified in the present study captures variance associated with additive genetics supporting the search for a genetically informed neural pain signature (Davis et al, 2020). Future studies should compare resting-state and pain-evoked functional connectivity and estimate the extent of their shared genetics and the neural targets of their shared and non-shared genes.…”
Section: Discussionsupporting
confidence: 69%
“…One major reason for the urgency of improving our understanding of the neural representations of pain is the opioid crisis, where opioid-based analgesics have created a wave of addiction, leading to overdoses and deaths. One review and a recent consensus paper by leading pain clinicians and scientists (Davis et al, 2020; Tracey, Woolf, & Andrews, 2019) explicitly ask for pain biomarkers– verifiable in preclinical models and patients. Stratification biomarkers may increase the probability of success in pharmacological clinical trials by as much as 21% in phase III clinical trials in all disease areas (Davis et al, 2020).…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…There remains a large gap in characterizing such power-band based biomarkers of naturalistic, spontaneous chronic pain; an sEEG trial can fill this gap. Ultimately, by combining recording with simultaneous stimulation in these areas, an sEEG trial period could inform adaptive DBS algorithms (for a thorough discussion of brain-based pain biomarkers see [ 42 , 54 ]).…”
Section: Detecting Biomarkers Of Chronic Pain and Stimulation-relamentioning
confidence: 99%
“…The search for an objective biomarker for pain intensity has been driven by a legitimate need to adequately assess pain in individuals who are unable to adequately communicate their firstperson experience of pain to a third person 26 , as well as to understand changes in such markers over time in response to disease or treatment [27][28][29][30] . However, there is also substantial pressure to use such markers to confirm the veracity of a patient's report of pain for legal and financial reasons 26,27,30,31 .…”
Section: Introductionmentioning
confidence: 99%