Covid19NCT04860895
Detection of SARS-CoV-2 in Nasopharyngeal Swabs by Using Multi-Spectral Screening System
A study testing AP-23 in people with Covid19, run by Fable Biyoteknoloji San ve Tic A.S at 1 site in Turkey (Türkiye).
Trial summary
The aim of this research is to use the Multi-Spectral method to measure the biomolecular fingerprint of the virus directly instead of the virus's RNA (RT-PCR) or the body's immune response (antibody) measurement methods to diagnose the SARS-COV-2 virus, thereby determining whether COVID-19 can be diagnosed faster… Read more about this study
- Who is it for?
- Ages 12 to 95 yearsHealthy volunteers can take part
- Conditions the study is for
- Covid19
- What is being tested?
- AP-23
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 4,400 participants
- Where
- 1 siteTurkey (Türkiye)
- Study dates
- 11 Feb 2021to 15 May 2021
- Phase
- Interventional
- Are there results?
- None posted in the registry
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 12 to 95 years
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Who may be able to join
- All people who applied to hospitals with suspicion of COVID-19
Who cannot join
- Person who cannot give nasopharyngeal samples
Trial locations and contacts
1 site in 1 country.
Turkey (Türkiye)1 site, 1 recruiting
- Recruiting
Sancaktepe Şehit Prof.Dr. İlhan Varank Training and Research Hospital
Sancaktepe, Istanbul, 34785
İsmail Tayfur, MD
About this study
Official title: The Reliability of the Computer Aided Multi-Spectral Screening System In the Diagnosis of Covid-19
The aim of this research is to use the Multi-Spectral method to measure the biomolecular fingerprint of the virus directly instead of the virus's RNA (RT-PCR) or the body's immune response (antibody) measurement methods to diagnose the SARS-COV-2 virus, thereby determining whether COVID-19 can be diagnosed faster, cheaper and without requiring a medical laboratory environment.
Read the detailed description
The primary purpose of this study is to test whether artificial intelligence (AI) will identify existing SARS-COV-2 in nasopharyngeal swab samples using multi-spectral screening technology..
Multi spectral screening testing device called AP-23 offers a non-invasive system for the diagnosis of SARS-COV-2 as a solution. This approach makes multi-spectral diagnostic methods suitable for use by any end user and allows the establishment of Internet of Things systems.
COVID-19 contagion, which began in the northern hemisphere, continues to affect human health and the world economy in tremendously. Early diagnosis of the disease and, accordingly, the breaking of the transmission chain through filiation studies is very important for public health until an effective and safe vaccine is found. PCR tests, which we currently use as the gold standard to prove the existence of the virus, have not been sufficient to prevent the pandemic for the following reasons;
- PCR tests should be performed in a hospital or clinical setting
- There is a need for a custom kit
- There is a need for trained individuals to perform the test
- Standardization is not ensured for the receipt of test sample
- With at least 30 minutes for receipt of the test results, it takes up to 3-day
- testing is expensive and is usually applied to people who have symptoms and thus asymptomatic carriers are missed.
The primary purpose of this study is to test whether SARS-COV-2 can be detected in nasopharyngeal swab samples using multi-spectral screening technology. Multi-spectral techniques are based on phenomena related to absorption, excitation and propagation of biomolecules. In short, by irradiating the sample with electromagnetic energy, some molecules absorb and re-emit less energetic radiation. This phenomenon is called radiation, and the radiated spectrum is a function of certain molecules that combine microorganisms / viruses.
At this point, FableCorp's AP-23 system uses data from a minimally invasive or non-invasive simple measurement based on multi-spectral screening technology to calculate the presence or concentration of the desired product in a biological liquid as the solution to be used.
The most unique approach of the FableCorp system, is to use the A.I. to detect the desired biochemical / cell / virus is to scan appropriate multi-spectral inputs. Data mining tools, where it simultaneously eliminates noise in raw data generated from various multi-spectral spectroscopy inputs, give very clear results. This approach makes multi-spectral technology suitable for use as point-of-care systems for any end user, and also leads to the realization of full automation (Internet of Things) systems.
A.I. the base solution for Pointer signal detection / processing eliminates biochemical additives (kits) and specialized personnel.
AI's evaluation of data takes place within 15-30 seconds. If the effectiveness of this application is proven in the diagnosis of SARS-COV-2, many more people will be able to be screened in a much faster time, much cheaper, and filiation will be applied to the necessary people much faster.
Study Design Stage 1: Nasopharyngeal samples taken from COVID-19 suspected individuals will be given to artificial intelligence to learn positive and negative cases, and the learning results will be calculated as the learning accuracy for negative and positive samples. (n=4000, 2000 positive and 2000 negative)
Stage 1, Output Parameters (Evaluation of Learning Performance of Artificial Intelligence):
PCR results and AP-23 results obtained as a result of comparison; PCR Accordance, PCR Accordance for Negative Samples, PCR Accordance for Positive Samples.
Stage 2: Based on the Artificial Intelligence Learning accuracy rate second stage of the study will be initiated. At this stage, Nasopharyngeal swab samples will be tested by PCR, AP-23, and the results will be tested and be compared and the sensitivity of detection compared with results obtained by (n=400, 200 positive and 200 negative)
Stage 2, Output Parameters (Evaluation of Test Performance of Artificial Intelligence):
Nasopharyngeal swab obtained by comparison with PCR and AP-23 results in samples; Sensitivity, Specificity, Negative Prediction Value, Positive Prediction Value.
- Conditions
- Covid19
- Being tested
- AP-23
- Keywords
- Artificial Intelligence, AI, SARS-COV2, Point of Care,
- Medical subject headings
- COVID-19
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AP-23Diagnostic test
AP-23 newly developed point of care system as a well-automated combination of multi-spectral technology and a distributed cloud computing A.I. system which has been developed to detect COVID-19.
| Study group | Role | What they receive |
|---|---|---|
| Nasopharyngeal swabs | Other | Nasopharyngeal swabs samples of volunteers who is referred with suspicion of Covid19. Receives: Diagnostic Test: AP-23 |
What is being measured
The primary outcome is the main question the study is designed to answer.
Assessment of AI's Learning Performance:
Compared PCR results with AP-23 results; PCR Accordance, PCR Accordance for Negative Samples, PCR Accordance for Positive Samples.
Measured: 2 MONTHS
Evaluation of Artificial Intelligence's Test Performance)
As a result of comparison with the PCR and AP-23 results in nasopharyngeal swab samples; Sensitiviy, Specificity, Negative Prediction Value, Positive Prediction Value
Measured: 1 MONTH
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 Apr 2021
- Study start11 Feb 2021
- Primary completion1 May 2021 (estimated)
- Study completion15 May 2021 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Covid19Studies of the same condition, open and under way.
- 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
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 4,400 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Fable Biyoteknoloji San ve Tic A.S
- Sponsor type
- Industry (pharma, biotech, devices)
- Responsible party
- Sponsor
- Investigators
- İsmail Tayfur, MD, Principal investigator, Sehit Prof. Dr. Ilhan Varank Sancaktepe Training and Research Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04860895
- Sponsor's protocol ID
- SNCKTP_AP-23
- Status last verified
- May 2021
- First submitted
- 25 Apr 2021
- Last updated
- 6 May 2021
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Tayfur I, Bayramoglu B, Guven R, Avci A. Diagnostic accuracy of artificial intelligence-based multi-spectrum analysis for molecular fingerprint detection of SARS-CoV-2. Medicine (Baltimore). 2025 May 23;104(21):e41928. doi: 10.1097/MD.0000000000041928.
PubMed 40419915
Study at a glance
From the registry record, last updated by the sponsor on 6 May 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- The Reliability of the Computer Aided Multi-Spectral Screening System In the Diagnosis of Covid-19
- ClinicalTrials.gov ID
- NCT04860895
- Acronym / sponsor ID
- SNCKTP_AP-23
- Conditions
- Covid19
- Keywords
- Artificial Intelligence, AI, SARS-COV2, Point of Care,
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 4,400 participants (estimated)
- Lead sponsor
- Fable Biyoteknoloji San ve Tic A.SIndustry (pharma, biotech, devices)
- Study start
- 11 Feb 2021 (actual)
- Primary completion
- 1 May 2021 (estimated)
- Study completion
- 15 May 2021 (estimated)
- First posted
- 27 Apr 2021 (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 aim of this research is to use the Multi-Spectral method to measure the biomolecular fingerprint of the virus directly instead of the virus's RNA (RT-PCR) or the body's immune response (antibody) measurement methods to diagnose the SARS-COV-2 virus, thereby determining whether COVID-19 can be diagnosed faster, cheaper and without requiring a medical laboratory environment.
Detailed description
The primary purpose of this study is to test whether artificial intelligence (AI) will identify existing SARS-COV-2 in nasopharyngeal swab samples using multi-spectral screening technology..
Multi spectral screening testing device called AP-23 offers a non-invasive system for the diagnosis of SARS-COV-2 as a solution. This approach makes multi-spectral diagnostic methods suitable for use by any end user and allows the establishment of Internet of Things systems.
COVID-19 contagion, which began in the northern hemisphere, continues to affect human health and the world economy in tremendously. Early diagnosis of the disease and, accordingly, the breaking of the transmission chain through filiation studies is very important for public health until an effective and safe vaccine is found. PCR tests, which we currently use as the gold standard to prove the existence of the virus, have not been sufficient to prevent the pandemic for the following reasons;
- PCR tests should be performed in a hospital or clinical setting
- There is a need for a custom kit
- There is a need for trained individuals to perform the test
- Standardization is not ensured for the receipt of test sample
- With at least 30 minutes for receipt of the test results, it takes up to 3-day
- testing is expensive and is usually applied to people who have symptoms and thus asymptomatic carriers are missed.
The primary purpose of this study is to test whether SARS-COV-2 can be detected in nasopharyngeal swab samples using multi-spectral screening technology. Multi-spectral techniques are based on phenomena related to absorption, excitation and propagation of biomolecules. In short, by irradiating the sample with electromagnetic energy, some molecules absorb and re-emit less energetic radiation. This phenomenon is called radiation, and the radiated spectrum is a function of certain molecules that combine microorganisms / viruses.
At this point, FableCorp's AP-23 system uses data from a minimally invasive or non-invasive simple measurement based on multi-spectral screening technology to calculate the presence or concentration of the desired product in a biological liquid as the solution to be used.
The most unique approach of the FableCorp system, is to use the A.I. to detect the desired biochemical / cell / virus is to scan appropriate multi-spectral inputs. Data mining tools, where it simultaneously eliminates noise in raw data generated from various multi-spectral spectroscopy inputs, give very clear results. This approach makes multi-spectral technology suitable for use as point-of-care systems for any end user, and also leads to the realization of full automation (Internet of Things) systems.
A.I. the base solution for Pointer signal detection / processing eliminates biochemical additives (kits) and specialized personnel.
AI's evaluation of data takes place within 15-30 seconds. If the effectiveness of this application is proven in the diagnosis of SARS-COV-2, many more people will be able to be screened in a much faster time, much cheaper, and filiation will be applied to the necessary people much faster.
Study Design Stage 1: Nasopharyngeal samples taken from COVID-19 suspected individuals will be given to artificial intelligence to learn positive and negative cases, and the learning results will be calculated as the learning accuracy for negative and positive samples. (n=4000, 2000 positive and 2000 negative)
Stage 1, Output Parameters (Evaluation of Learning Performance of Artificial Intelligence):
PCR results and AP-23 results obtained as a result of comparison; PCR Accordance, PCR Accordance for Negative Samples, PCR Accordance for Positive Samples.
Stage 2: Based on the Artificial Intelligence Learning accuracy rate second stage of the study will be initiated. At this stage, Nasopharyngeal swab samples will be tested by PCR, AP-23, and the results will be tested and be compared and the sensitivity of detection compared with results obtained by (n=400, 200 positive and 200 negative)
Stage 2, Output Parameters (Evaluation of Test Performance of Artificial Intelligence):
Nasopharyngeal swab obtained by comparison with PCR and AP-23 results in samples; Sensitivity, Specificity, Negative Prediction Value, Positive Prediction Value.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Nasopharyngeal swabs | Other | Diagnostic Test: AP-23Nasopharyngeal swabs samples of volunteers who is referred with suspicion of Covid19. |
Who may qualify
- Ages
- 12 to 95 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (1 listed)
- All people who applied to hospitals with suspicion of COVID-19
Key exclusion criteria (1 listed)
- Person who cannot give nasopharyngeal samples
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 |
|---|---|---|
| AP-23AP-23 newly developed point of care system as a well-automated combination of multi-spectral technology and a distributed cloud computing A.I. system which has been developed to detect COVID-19. | Diagnostic test | Nasopharyngeal swabs |
Primary outcome
Assessment of AI's Learning Performance:
Time frame: 2 MONTHS
Compared PCR results with AP-23 results; PCR Accordance, PCR Accordance for Negative Samples, PCR Accordance for Positive Samples.
Evaluation of Artificial Intelligence's Test Performance)
Time frame: 1 MONTH
As a result of comparison with the PCR and AP-23 results in nasopharyngeal swab samples; Sensitiviy, Specificity, Negative Prediction Value, Positive Prediction Value
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 6 May 2021.
- Derived from this study: PubMed 40419915Tayfur I, Bayramoglu B, Guven R, Avci A. Diagnostic accuracy of artificial intelligence-based multi-spectrum analysis for molecular fingerprint detection of SARS-CoV-2. Medicine (Baltimore). 2025 May 23;104(21):e41928. doi: 10.1097/MD.0000000000041928.
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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. This study is not recruiting at the moment.
İsmail Tayfur, MD principal investigator
Sehit Prof. Dr. Ilhan Varank Sancaktepe Training and Research Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AP-23 in people with Covid19, run by Fable Biyoteknoloji San ve Tic A.S at 1 site in Turkey (Türkiye).
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: status not confirmed, as of the sponsor's last update on 6 May 2021. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Turkey (Türkiye). 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?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Deniz Unver, MSc. (+905380246808, deniz.unver@fablecorp.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Assessment of AI's Learning Performance: (time frame: 2 MONTHS). The study lists 2 primary outcomes in all. 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 NCT04860895, which also lists 1 linked publication.
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 6 May 2021.