Congenital DisorderCLIP-AINCT06970158
Clinical Application of Artificial Intelligence in New Borns With Cleft Lip and Palate
A study testing AI-Designed Passive Plate Therapy in people with Congenital Disorder and Cleft Lip Palate, run by University Hospital, Basel, Switzerland at 2 sites in India.
Trial summary
The goal of this observational study is to evaluate whether passive plate therapy using automated AI-designed devices can reduce cleft size in newborns with cleft lip and palate. Read more about this study
- Who is it for?
- Ages 1 day to 6 months
- Conditions the study is for
- Congenital Disorder, Cleft Lip Palate
- What is being tested?
- AI-Designed Passive Plate Therapy
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 70 participants
- Where
- 2 sitesIndia
- Study dates
- 1 Aug 2023to 31 Dec 2025
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 1 day to 6 months
- All sexes
- No healthy volunteers
- Child
Who may be able to join
- Infants diagnosed with unilateral cleft lip and palate Age at enrollment: within the first 14 days of life (for treatment group) Age at cleft surgery: approximately 4 months Medically stable and fit to undergo intraoral scanning and cleft surgery Parent or legal guardian has provided written informed consent
Who cannot join
- Syndromic cleft lip and palate or other craniofacial syndromes Bilateral cleft lip and palate Significant comorbidities affecting feeding, growth, or surgery (e.g., cardiac anomalies) Premature infants (<37 weeks gestational age at birth) Infants who have already undergone any presurgical orthopedic intervention elsewhere Guardians/ Parents unwilling or unable to comply with follow-up or study procedures
Trial locations and contacts
2 sites in 1 country. Contact the study team or a site near you to ask about taking part.
India2 sites, 2 recruiting
- Recruiting
Saveetha Medical College
Chennai, 602105
Praveen Ganesh Prof. Dr., MDS, FDS RCPS, +919972152140, prgfacsurg@gmail.com
Praveen Ganesh Prof. Dr. Ganesh, MDS, FDS RCPS
- Recruiting
GSR Hospital Hyderabad
Hyderabad, 500059
Hemwati Nandan, MDS, +919997703789, hemwatinandanbahuguna@gmail.com
Srinivas Gosla Prof. Dr. Reddy, MBBS, MDS, Phd
About this study
Official title: Effect of Automated AI Designed Presurgical Plate Therapy on Cleft Size Reduction in Newborns With Cleft Lip and Palate : A Comparative Study
The goal of this observational study is to evaluate whether passive plate therapy using automated AI-designed devices can reduce cleft size in newborns with cleft lip and palate. The main questions it aims to answer are:
Does AI-designed passive plate therapy reduce the cleft size between birth and primary surgery? (Primary aim)
Read more
How does cleft size at the time of surgery compare between infants who received passive plate therapy and those who did not? (Secondary aim)
Researchers will compare infants who received AI-designed passive plate therapy with those who received no presurgical therapy to determine whether the intervention leads to a greater reduction in cleft width.
Participants will: Undergo intraoral scans at birth and again at the time of primary surgery, around 4 months of age.
Receive either no presurgical intervention or be treated with AI-designed passive plates, depending on site-specific clinical practices
Read the detailed description
This observational study investigates the impact of passive plate therapy using an automated, artificial intelligence (AI)-driven design workflow on presurgical cleft size in infants with unilateral cleft lip and palate. Cleft lip and palate represent one of the most common congenital craniofacial anomalies, and early presurgical interventions such as passive plates aim to reduce the cleft size, support feeding, and facilitate better surgical outcomes. However, access to such interventions is often limited by the need for specialized staff, complex workflows, and reliance on intraoral impressions.
Recent technological advancements have enabled the integration of digital workflows and AI into presurgical cleft care. In particular, a pipeline has been developed that uses intraoral scanning, and AI-assisted modeling to design individualized passive plates. These plates are manufactured via 3D printing and do not require invasive impressions nor extensive laboratory work making them potentially safer and more scalable in low or medium resource settings.
This study specifically evaluates the clinical effectiveness of such AI-designed passive plates compared to standard care without any presurgical orthopedic therapy. Infants are enrolled from two sites in India (Chennai and Hyderabad), where clinical practices differ with respect to the use of passive plates. As this is a non-randomized, observational study, group assignment is based on local standard of care at each site.
The primary objective is to assess the percentage reduction in cleft width from birth to the time of primary surgery (typically around 4 months of age) in infants treated with AI-designed passive plates. The secondary objective is to compare cleft width at the time of surgery between infants who received the plates and those who did not, offering insight into the relative anatomical outcomes of the intervention.
All participating infants will undergo standardized intraoral scans at baseline (within the first two weeks of life) and again just prior to primary surgical repair. The scans are used to measure the anterior-posterior cleft width and calculate percentage change over time. Cleft measurements are obtained digitally from 3D scan data using validated image processing software.
The AI-assisted design of the passive plates is performed using a custom plugin within Blender software, which automatically detects anatomical landmarks and generates the plate geometry with minimal user input. The digital files are subsequently exported for 3D printing using biocompatible materials. Infants in the intervention group will wear the plate continuously from the time of fitting until primary surgery, under the supervision of trained clinical teams.
Data from the two cohorts (plate vs. no plate) will be compared using appropriate statistical methods to assess differences in cleft size reduction and absolute cleft width at surgery. This study does not include randomization or blinding, as the intervention is assigned based on institutional practice. However, efforts will be made to ensure consistency in scanning methods, measurement protocols, and outcome assessment across both sites.
This study is part of a larger initiative to evaluate the generalizability and effectiveness of AI-based digital workflows in cleft care across diverse healthcare settings. The findings are expected to inform future integration of automated design technologies in presurgical treatment planning, especially in regions where access to skilled cleft teams is limited.
No additional interventions, medications, or behavioral changes are introduced as part of this study. Participation involves routine procedures and follow-up through the standard cleft treatment timeline.
- Conditions
- Congenital Disorder, Cleft Lip Palate
- Being tested
- AI-Designed Passive Plate Therapy
- Keywords
- artificial intelligence, Cleft Lip Palate
- Medical subject headings
- Congenital, Hereditary, and Neonatal Diseases and Abnormalities
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-Designed Passive Plate TherapyOther
Also called Automated Passive Plate
A removable passive orthopedic plate designed using an AI-assisted digital workflow based on intraoral scan data. The design process is automated via a Blender-based software plugin that identifies anatomical landmarks and generates a custom-fit plate. The plate is 3D printed using biocompatible material and fitted shortly after birth. It is worn continuously until primary surgical repair, typically around 4 months of age. The intervention aims to reduce cleft width prior to surgery without requiring traditional impressions or extensive manual design effort.
| Study group | Role | What they receive |
|---|---|---|
| AI-Designed Passive Plate Therapy | Experimental | Infants in this group will receive passive plate therapy designed using an AI-assisted digital workflow. The plate is fitted shortly after birth and worn continuously until the time of primary surgical repair (around 4 months of age). Participants in this arm will undergo intraoral scans at birth and again at surgery. Receives: Other: AI-Designed Passive Plate Therapy |
| No Presurgical Therapy | No intervention | Infants in this group will not receive any presurgical orthopedic intervention. They will undergo a single intraoral scan at the time of primary surgical repair (around 4 months of age), which will be used for comparison with the intervention group. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Percent Reduction in Cleft Width from Birth to Primary Surgery
Measured as the percentage change in anterior-posterior cleft width between the intraoral scan at birth and the scan at the time of primary surgery (~4 months), in infants receiving AI-designed passive plate therapy.
Measured: From birth to time of primary cleft surgery (approximately 4 months of age)
Secondary outcomes (1)
Cleft Width at Time of Primary Surgery
Absolute cleft width (in mm) at the time of primary surgery, measured from intraoral scan data. This will be compared between infants who received AI-designed passive plates and those who received no presurgical therapy.
Measured: At the time of primary cleft surgery (approximately 4 months of age)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted14 May 2025
- Study start1 Aug 2023
- Primary completion1 Aug 2025 (estimated)
- Study completion31 Dec 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (5)Papers the sponsor has linked to this study.
- Other trials for Congenital DisorderStudies of the same condition, open and under way.
- More trials run by University Hospital, Basel, SwitzerlandThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Treatment
- Allocation
- Non-randomised
- Intervention model
- Parallel groups
- Model description
- Participants will be assigned to one of two groups based on clinical site practices. The treatment group will receive AI-designed passive plate therapy from shortly after birth until primary surgery and will undergo intraoral scans at birth and at approximately 4 months of age. The comparison group will receive no presurgical intervention and will undergo a single intraoral scan at the time of primary surgery (around 4 months). This parallel design allows for evaluation of cleft size at surgery between treated and untreated groups.
- Masking
- None (open label)
- Enrolment
- 70 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University Hospital, Basel, Switzerland
- Sponsor type
- University, hospital or other
- Collaborators
- University of Basel
- Responsible party
- Principal investigator, Prasad Nalabothu, University Hospital, Basel, Switzerland
- Investigators
- Andreas Mueller, PhD,MHBA, Study chair, University Hospital, Basel, SwitzerlandPrasad Nalabothu, MDS PhD, Principal investigator, University Hospital, Basel, Switzerland
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06970158
- Sponsor's protocol ID
- placeholder unique ID
- Acronym
- CLIP-AI
- Status last verified
- May 2025
- First submitted
- 7 May 2024
- Last updated
- 16 May 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: De-identified individual participant data (IPD) that underlie the results reported in publications will be shared, including cleft width measurements at birth and at surgery, group assignment, and relevant demographic and clinical variables. A data dictionary defining each variable will be provided. Data will be made available after publication of the primary results upon reasonable request to the study sponsor or principal investigator.
Publications
Nalabothu P, Benitez BK, Dalstra M, Verna C, Mueller AA. Three-Dimensional Morphological Changes of the True Cleft under Passive Presurgical Orthopaedics in Unilateral Cleft Lip and Palate: A Retrospective Cohort Study. J Clin Med. 2020 Mar 31;9(4):962. doi: 10.3390/jcm9040962.
PubMed 32244361Benitez BK, Brudnicki A, Surowiec Z, Wieprzowski L, Rasadurai A, Nalabothu P, Lill Y, Mueller AA. Digital impressions from newborns to preschoolers with cleft lip and palate: A two-centers experience. J Plast Reconstr Aesthet Surg. 2022 Nov;75(11):4233-4242. doi: 10.1016/j.bjps.2022.08.015. Epub 2022 Aug 22.
PubMed 36154982Zarean P, Zarean P, Thieringer FM, Mueller AA, Kressmann S, Erismann M, Sharma N, Benitez BK. A Point-of-Care Digital Workflow for 3D Printed Passive Presurgical Orthopedic Plates in Cleft Care. Children (Basel). 2022 Aug 20;9(8):1261. doi: 10.3390/children9081261.
PubMed 36010151Meyer S, Benitez BK, Thieringer FM, Mueller AA. Three-Dimensional Printable Open-Source Cleft Lip and Palate Impression Trays: A Single-Impression Workflow. Plast Reconstr Surg. 2024 Feb 1;153(2):462-465. doi: 10.1097/PRS.0000000000010684. Epub 2023 May 15.
PubMed 37184464Schnabel TN, Gozcu B, Gotardo P, Lingens L, Dorda D, Vetterli F, Emhemmed A, Nalabothu P, Lill Y, Benitez BK, Mueller AA, Gross M, Solenthaler B. Automated and data-driven plate computation for presurgical cleft lip and palate treatment. Int J Comput Assist Radiol Surg. 2023 Jun;18(6):1119-1125. doi: 10.1007/s11548-023-02858-6. Epub 2023 Apr 2.
PubMed 37009952
Study at a glance
From the registry record, last updated by the sponsor on 16 May 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Effect of Automated AI Designed Presurgical Plate Therapy on Cleft Size Reduction in Newborns With Cleft Lip and Palate : A Comparative Study
- ClinicalTrials.gov ID
- NCT06970158
- Acronym / sponsor ID
- CLIP-AI / placeholder unique ID
- Conditions
- Congenital Disorder, Cleft Lip Palate
- Keywords
- artificial intelligence, Cleft Lip Palate
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 70 participants (estimated)
- Lead sponsor
- University Hospital, Basel, SwitzerlandUniversity, hospital or other
- Collaborators
- University of Basel
- Study start
- 1 Aug 2023 (actual)
- Primary completion
- 1 Aug 2025 (estimated)
- Study completion
- 31 Dec 2025 (estimated)
- First posted
- 14 May 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The goal of this observational study is to evaluate whether passive plate therapy using automated AI-designed devices can reduce cleft size in newborns with cleft lip and palate. The main questions it aims to answer are:
Does AI-designed passive plate therapy reduce the cleft size between birth and primary surgery? (Primary aim)
How does cleft size at the time of surgery compare between infants who received passive plate therapy and those who did not? (Secondary aim)
Researchers will compare infants who received AI-designed passive plate therapy with those who received no presurgical therapy to determine whether the intervention leads to a greater reduction in cleft width.
Participants will: Undergo intraoral scans at birth and again at the time of primary surgery, around 4 months of age.
Receive either no presurgical intervention or be treated with AI-designed passive plates, depending on site-specific clinical practices
Detailed description
This observational study investigates the impact of passive plate therapy using an automated, artificial intelligence (AI)-driven design workflow on presurgical cleft size in infants with unilateral cleft lip and palate. Cleft lip and palate represent one of the most common congenital craniofacial anomalies, and early presurgical interventions such as passive plates aim to reduce the cleft size, support feeding, and facilitate better surgical outcomes. However, access to such interventions is often limited by the need for specialized staff, complex workflows, and reliance on intraoral impressions.
Recent technological advancements have enabled the integration of digital workflows and AI into presurgical cleft care. In particular, a pipeline has been developed that uses intraoral scanning, and AI-assisted modeling to design individualized passive plates. These plates are manufactured via 3D printing and do not require invasive impressions nor extensive laboratory work making them potentially safer and more scalable in low or medium resource settings.
This study specifically evaluates the clinical effectiveness of such AI-designed passive plates compared to standard care without any presurgical orthopedic therapy. Infants are enrolled from two sites in India (Chennai and Hyderabad), where clinical practices differ with respect to the use of passive plates. As this is a non-randomized, observational study, group assignment is based on local standard of care at each site.
The primary objective is to assess the percentage reduction in cleft width from birth to the time of primary surgery (typically around 4 months of age) in infants treated with AI-designed passive plates. The secondary objective is to compare cleft width at the time of surgery between infants who received the plates and those who did not, offering insight into the relative anatomical outcomes of the intervention.
All participating infants will undergo standardized intraoral scans at baseline (within the first two weeks of life) and again just prior to primary surgical repair. The scans are used to measure the anterior-posterior cleft width and calculate percentage change over time. Cleft measurements are obtained digitally from 3D scan data using validated image processing software.
The AI-assisted design of the passive plates is performed using a custom plugin within Blender software, which automatically detects anatomical landmarks and generates the plate geometry with minimal user input. The digital files are subsequently exported for 3D printing using biocompatible materials. Infants in the intervention group will wear the plate continuously from the time of fitting until primary surgery, under the supervision of trained clinical teams.
Data from the two cohorts (plate vs. no plate) will be compared using appropriate statistical methods to assess differences in cleft size reduction and absolute cleft width at surgery. This study does not include randomization or blinding, as the intervention is assigned based on institutional practice. However, efforts will be made to ensure consistency in scanning methods, measurement protocols, and outcome assessment across both sites.
This study is part of a larger initiative to evaluate the generalizability and effectiveness of AI-based digital workflows in cleft care across diverse healthcare settings. The findings are expected to inform future integration of automated design technologies in presurgical treatment planning, especially in regions where access to skilled cleft teams is limited.
No additional interventions, medications, or behavioral changes are introduced as part of this study. Participation involves routine procedures and follow-up through the standard cleft treatment timeline.
Study design
- Primary purpose
- Treatment
- Allocation
- Non-randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
- Model description
- Participants will be assigned to one of two groups based on clinical site practices. The treatment group will receive AI-designed passive plate therapy from shortly after birth until primary surgery and will undergo intraoral scans at birth and at approximately 4 months of age. The comparison group will receive no presurgical intervention and will undergo a single intraoral scan at the time of primary surgery (around 4 months). This parallel design allows for evaluation of cleft size at surgery between treated and untreated groups.
| Arm | Type | Receives |
|---|---|---|
| AI-Designed Passive Plate Therapy | Experimental | Other: AI-Designed Passive Plate TherapyInfants in this group will receive passive plate therapy designed using an AI-assisted digital workflow. The plate is fitted shortly after birth and worn continuously until the time of primary surgical repair (around 4 months of age). Participants in this arm will undergo intraoral scans at birth and again at surgery. |
| No Presurgical Therapy | No intervention | –Infants in this group will not receive any presurgical orthopedic intervention. They will undergo a single intraoral scan at the time of primary surgical repair (around 4 months of age), which will be used for comparison with the intervention group. |
Who may qualify
- Ages
- 1 day to 6 months
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child
Key inclusion criteria (1 listed)
- Infants diagnosed with unilateral cleft lip and palate Age at enrollment: within the first 14 days of life (for treatment group) Age at cleft surgery: approximately 4 months Medically stable and fit to undergo intraoral scanning and cleft surgery Parent or legal guardian has provided written informed consent
Key exclusion criteria (1 listed)
- Syndromic cleft lip and palate or other craniofacial syndromes Bilateral cleft lip and palate Significant comorbidities affecting feeding, growth, or surgery (e.g., cardiac anomalies) Premature infants (<37 weeks gestational age at birth) Infants who have already undergone any presurgical orthopedic intervention elsewhere Guardians/ Parents unwilling or unable to comply with follow-up or study procedures
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI-Designed Passive Plate TherapyAlso: Automated Passive PlateA removable passive orthopedic plate designed using an AI-assisted digital workflow based on intraoral scan data. The design process is automated via a Blender-based software plugin that identifies anatomical landmarks and generates a custom-fit plate. The plate is 3D printed using biocompatible material and fitted shortly after birth. It is worn continuously until primary surgical repair, typically around 4 months of age. The intervention aims to reduce cleft width prior to surgery without requiring traditional impressions or extensive manual design effort. | Other | AI-Designed Passive Plate Therapy |
Primary outcome
Percent Reduction in Cleft Width from Birth to Primary Surgery
Time frame: From birth to time of primary cleft surgery (approximately 4 months of age)
Measured as the percentage change in anterior-posterior cleft width between the intraoral scan at birth and the scan at the time of primary surgery (~4 months), in infants receiving AI-designed passive plate therapy.
1 secondary outcome
Cleft Width at Time of Primary Surgery
Time frame: At the time of primary cleft surgery (approximately 4 months of age)
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 16 May 2025.
- Results publication: PubMed 32244361Nalabothu P, Benitez BK, Dalstra M, Verna C, Mueller AA. Three-Dimensional Morphological Changes of the True Cleft under Passive Presurgical Orthopaedics in Unilateral Cleft Lip and Palate: A Retrospective Cohort Study. J Clin Med. 2020 Mar 31;9(4):962. doi: 10.3390/jcm9040962.
- Results publication: PubMed 36154982Benitez BK, Brudnicki A, Surowiec Z, Wieprzowski L, Rasadurai A, Nalabothu P, Lill Y, Mueller AA. Digital impressions from newborns to preschoolers with cleft lip and palate: A two-centers experience. J Plast Reconstr Aesthet Surg. 2022 Nov;75(11):4233-4242. doi: 10.1016/j.bjps.2022.08.015. Epub 2022 Aug 22.
- Results publication: PubMed 36010151Zarean P, Zarean P, Thieringer FM, Mueller AA, Kressmann S, Erismann M, Sharma N, Benitez BK. A Point-of-Care Digital Workflow for 3D Printed Passive Presurgical Orthopedic Plates in Cleft Care. Children (Basel). 2022 Aug 20;9(8):1261. doi: 10.3390/children9081261.
- Results publication: PubMed 37184464Meyer S, Benitez BK, Thieringer FM, Mueller AA. Three-Dimensional Printable Open-Source Cleft Lip and Palate Impression Trays: A Single-Impression Workflow. Plast Reconstr Surg. 2024 Feb 1;153(2):462-465. doi: 10.1097/PRS.0000000000010684. Epub 2023 May 15.
- Results publication: PubMed 37009952Schnabel TN, Gozcu B, Gotardo P, Lingens L, Dorda D, Vetterli F, Emhemmed A, Nalabothu P, Lill Y, Benitez BK, Mueller AA, Gross M, Solenthaler B. Automated and data-driven plate computation for presurgical cleft lip and palate treatment. Int J Comput Assist Radiol Surg. 2023 Jun;18(6):1119-1125. doi: 10.1007/s11548-023-02858-6. Epub 2023 Apr 2.
- Individual participant dataSharing planned: Yes. De-identified individual participant data (IPD) that underlie the results reported in publications will be shared, including cleft width measurements at birth and at surgery, group assignment, and relevant demographic and clinical variables. A data dictionary defining each variable will be provided. Data will be made available after publication of the primary results upon reasonable request to the study sponsor or principal investigator.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Andreas Mueller, PhD,MHBA study chair
University Hospital, Basel, Switzerland
Prasad Nalabothu, MDS PhD principal investigator
University Hospital, Basel, Switzerland
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI-Designed Passive Plate Therapy in people with Congenital Disorder and Cleft Lip Palate, run by University Hospital, Basel, Switzerland at 2 sites in India.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 16 May 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in India. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Prasad Nalabothu, PhD (+41765014420, p.nalabothu@usb.ch), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Percent Reduction in Cleft Width from Birth to Primary Surgery (time frame: From birth to time of primary cleft surgery (approximately 4 months of age)). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06970158, which also lists 5 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 16 May 2025.