7 Ways of Accelerating Dermatology Clinical Trials with AI: Faster Database Lock with Superior Data Quality

In the race to bring new dermatology treatments to market, every week counts. Clinical trial sponsors face the critical challenge of accelerating timelines while enhancing data quality for regulatory submissions.

Whether you're a pharmaceutical company, biotech, or CRO, Legit.Health's AI-powered platform delivers what matters most: faster database lock, 15% increase in data completeness, and regulatory-grade data quality increased inter-rater reliability.

A few years ago, we wrote a blog post in which explained 7 ways our AI technology improves dermatology clinical trials. Since then, we have learned a lot from working with pharmaceutical companies, biotechs, and CROs worldwide. Thus, we decided to update you with a new version.

Here are the 7 ways Legit.Health accelerates your dermatology clinical trials

• 1. Accelerated Site Startup: Faster Training with Superior Protocol Adherence
• 2. Streamlined Workflows Attract More Sites
• 3. Superior Data Quality: 15% Increased Inter-Rater Reliability
• 4. Real-Time Site Monitoring: Reduce Risk & Improve Oversight
• 5. Faster Database Lock
• 6. Overall Time-to-Market Acceleration
• 7. Stronger Regulatory Evidence
• Bonus: Competitive Differentiator in Site Recruitment
• Frequently Asked Questions
• Summary
• References

This is a strategic overview for clinical operations, biostatistics, medical affairs, and executive stakeholders, demonstrating how AI technology directly accelerates your path to market while strengthening your regulatory submission package.

1. Accelerated Site Startup: Faster Training with Superior Protocol Adherence

TL;DR

Legit.Health accelerates site activation from weeks to days with faster training. The platform ensures an increase in data completeness and eliminates scoring variability with automated, validated algorithms. Sites can begin enrolling patients earlier, directly accelerating your trial timeline while maintaining superior data quality for regulatory submissions.

Challenges

• Dermatology-focused trials often require specialised sites because image capture and scoring (e.g., severity indices) are highly specific and subtle.
• Manual severity scoring systems (PASI, EASI, SCORAD, HiSCR, IHS4, IGA, GAGS, VASI, etc.) are tedious and prone to variability and missing data.
• Sites may discard patients or drop data when scoring definitions are unclear or too time-consuming, reducing usable dataset size and increasing risk of protocol deviations.

Solution

Legit.Health's AI automates scoring of several established dermatology severity indices. For example, the platform supports an automatic measurement of EASI and SCORAD for atopic dermatitis¹, as well as HiSCR and IHS4 for hidradenitis suppurativa², SALT for alopecia, PASI for psoriasis³, and others.

As you can see in the video below, the AI automatically detects and counts acne lesions, calculating severity scores in real time during the patient visit. Then, the investigator simply verifies or adjusts the AI's output before submission, reducing time and cognitive burden.

Real-time demonstration of Legit.Health's AI technology. Just by looking at the image, the AI automatically counts acne lesions. The, the investigator may override the result. This automated approach reduces investigator burden and improves data quality in dermatology clinical research.

It also offers image-quality assessment in real time via its DIQA (Dermatology Image Quality Assessment) algorithm, ensuring that captured images meet the required standard for clinical-trial use.

By reducing the cognitive and manual burden on investigators and site staff, the platform helps improve adherence to the protocol scoring workflows and reduces the chance of incomplete or missing scoring data.

With fewer discarded or incomplete cases, the sponsor has a cleaner dataset, higher statistical power, and more reliable endpoints.

2. Streamlined Workflows Attract More Sites

TL;DR

Legit.Health enables sites to see more patients per day with a reduction in assessment time (3-5 minutes vs 15-25 minutes per patient). This efficiency attracts 50% more sites to participate, accelerating enrollment from 15 to 25+ patients per site per month. Faster recruitment means reaching your enrollment target months earlier, directly accelerating time to market.

Challenge

• Dermatologists are busy clinicians. The requirement to manually complete scoring systems, capture and upload images in specific ways, and manage additional trial workflows can be a deterrent to participation.
• Investigator time is a cost for the sponsor (site budget) and a barrier to site start-up and retention.

Solution

The AI automates scoring, so investigators do not have to manually compute scoring indices: instead they simply verify the AI's output and adjust if necessary. This means reduced time per patient visit devoted to trial scoring and documentation, freeing the investigator to focus on clinical aspects of the trial.

Automated IHS4 scoring demonstration for Hidradenitis Suppurativa clinical trials². The AI automatically detects and classifies nodules, abscesses, and draining tunnels, providing objective endpoint measurements that reduce inter-rater variability and support regulatory submissions.

From a recruitment standpoint, the reduced burden and streamlined workflow make the trial more attractive to dermatologists who otherwise might decline to participate.

The platform thus supports faster site start-up, better investigator engagement, and lower site dropout risk.

3. Superior Data Quality: 15% Increased Inter-Rater Reliability

TL;DR

Legit.Health delivers regulatory-grade data quality with 85-95% inter-rater reliability (vs 65-75% manual), 95%+ data completeness, and 77% fewer image quality issues. This superior data quality strengthens your statistical power by 15-25%, reduces regulatory queries, and accelerates approval timelines. Every endpoint is backed by peer-reviewed validation studies, ensuring your submission meets the highest regulatory standards.

Challenge

• Manual scoring systems are subject to inter- and intra-observer variability. Inconsistencies in how investigators compute severity indices can reduce the reliability of key endpoints and introduce noise into trial data.
• Image capture (lighting, focus, framing) may vary across sites, reducing comparability across patients and time-points.
• Incomplete or inconsistent data (missing visits, missing scores, poor image quality) can force sponsors into data cleaning, imputation, or exclusion of subjects — all of which compromise power and increase costs.

Solution

• The AI's automated severity scoring delivers objective, reproducible measurements directly from dermatological images, reducing variability. Specifically, the research articles Automatic International Hidradenitis Suppurativa...², Automatic SCOring of Atopic Dermatitis¹ or Automatic Psoriasis Area and Severity Index...³ demonstrate the accuracy and reliability of these automated scores.
• The image quality check (DIQA)⁴ ensures that images meet standard conditions before they are scored, improving consistency across sites.
• Standardised workflows across sites mean that the sponsor enjoys more harmonised data, which simplifies analysis, reduces variability, and supports stronger statistical conclusions.
• As a consequence, the credibility of the endpoint measurement is enhanced, supporting regulatory and publication quality of outcomes.

For clinical trial sponsors and CROs, this translates directly to improved patient retention rates and better site engagement. By reducing the administrative burden, sponsors can allocate clinical trial budgets more efficiently, investing saved costs into expanding recruitment or adding additional endpoints.

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4. Real-Time Site Monitoring: Reduce Risk & Improve Oversight

TL;DR

Legit.Health gives you monitoring-grade transparency into how each site is performing in terms of image capture, scoring completeness and protocol adherence. You can identify and correct issues early, reducing the risk of data loss, deviations or drop-outs. Monitoring becomes more efficient and effective with built-in analytics rather than waiting for the end of the study to detect problems.

Challenge

• Sponsors need to ensure that sites are capturing images correctly, following the protocol, and that scoring is being done fully, often a monitoring burden (onsite visits, remote review).
• Sites may drift from protocol, image quality may degrade, or data may be incomplete without early detection.

Solution

• Because images and scoring are processed through the platform, sponsors can gain transparency into site performance (image quality metrics, scoring completeness, verification rates).
• Early detection of sub-optimal image capture or scoring compliance allows corrective action (site retraining, query management) before major data loss occurs.
• This supports better site oversight, fewer surprises at database lock, and lower monitoring costs (fewer required visits if remote metrics show compliance).

5. Faster Database Lock

TL;DR

Legit.Health delivers database lock 4-6 weeks faster through immediate data availability, fewer queries, and an increase in first-pass data quality. Real-time data flow enables interim analyses 30% earlier, supporting adaptive trial designs and faster go/no-go decisions. This acceleration translates directly to earlier market entry and competitive advantage.

Challenge

• Manual scoring and image workflows often introduce delays: scoring must be done, images uploaded, queries resolved, monitors review, etc. These delays can slow interim analyses and final read-outs.
• Site start-up may be lengthened by training requirements for image capture and scoring systems.

Solution

• The streamlined workflow (image capture → automatic scoring → investigator verification) reduces time per subject, and speeds up site throughput.

• Reduced investigator burden and simplified training lead to faster site start-up and fewer drop-outs.
• Faster, standardised data flow supports quicker interim look-outs, cleaner database lock and potentially faster regulatory filings.

For clinical trial sponsors and CROs, the platform's seamless integration with EDC systems and support for ePRO workflows enables decentralized clinical trial models, allowing sponsors to reach broader patient populations while maintaining data integrity. This DCT-friendly approach is particularly valuable for sponsors seeking to reduce site-related costs and accelerate enrollment timelines.

6. Overall Time-to-Market Acceleration

TL;DR

Legit.Health accelerates your dermatology trial by months through faster site activation, accelerated recruitment, and earlier database lock. The platform delivers 85-95% data quality metrics that strengthen regulatory submissions, reduce queries by 60%, and increase first-pass approval rates. Time-to-market acceleration alone can be worth $50-100M in additional revenue for blockbuster drugs.

Challenge

• For a drug with $1B annual potential, each week of delay costs approximately $20M in lost revenue.
• Traditional clinical trials face lengthy timelines across site activation, recruitment, and database lock phases.
• Data quality issues (70-80% first-pass quality, high variability) lead to regulatory queries and review delays.

Solution

Legit.Health accelerates your timeline at every critical phase. Site activation happens weeks faster thanks to reduced training requirements. Patient recruitment accelerates as more sites participate and enrollment rates improve. Database lock comes sooner through immediate data availability and fewer queries requiring resolution. Regulatory review proceeds more smoothly when data quality is superior from the start.

The platform delivers data quality that directly supports faster approval. First-pass data quality improves significantly compared to industry standards, which means fewer queries from regulators and stronger statistical power through reduced variability. Peer-reviewed validation of the AI algorithms provides the scientific foundation that strengthens regulatory submissions.

Beyond timeline acceleration, the platform enables strategic advantages that compound over time. Real-time data availability supports adaptive trial designs with faster protocol modifications when needed. DCT capabilities expand your reach to larger patient pools, while the streamlined workflow attracts more sites to participate. Perhaps most importantly, the learnings and efficiencies gained apply across your entire dermatology trial portfolio.

7. Stronger Regulatory Evidence

TL;DR

Your dermatology trial endpoints can be powered by a clinically-validated AI, supporting your IO, regulatory submission and publication strategy. By leveraging a validated tool you reduce data-quality risk and strengthen your trial's scientific credibility.”

Challenge

• Dermatology endpoints are often criticised for subjectivity; regulators and publications increasingly value objective, reproducible measures.
• Data completeness, standardisation and robustness of scoring help strengthen submissions.

Solution

Legit.Health has published peer-reviewed validation studies covering severity-scoring automation for major dermatological conditions. These include automated scoring systems for atopic dermatitis¹, hidradenitis suppurativa², psoriasis³, and urticaria⁵. The platform also includes a validated image quality assessment system (DIQA) that ensures captured images meet the required standard for clinical trial use⁴. Additionally, research has demonstrated the utility of Legit.Health's deep learning algorithms for diagnostic support in skin malignancies⁶.

Using a validated platform supports regulatory confidence and publication credibility through objective measures, standardised workflows, and peer-reviewed backing.

Bonus: Competitive Differentiator in Site Recruitment

TL;DR

By including Legit.Health in your trial design you differentiate your study in site selection meetings: dermatologists will appreciate the streamlined, modern workflow. This helps you recruit top sites faster, improve site satisfaction, and potentially secure more competitive budgets.

Challenge

• Dermatology trial recruitment is competitive; sites often choose between multiple trials and may pick those with lower administrative burden, higher support, fewer additional scoring burdens.
• Sponsors who can offer streamlined workflows and investigator-friendly tools have a competitive edge.

Solution

• Offering Legit.Health as part of your trial protocol makes your study more attractive to dermatologists: less manual work, efficient scoring, high-quality data capture.
• You position yourself as innovation-oriented and supportive of investigator workflow.
• This can expand your pool of available sites, improve investigator satisfaction, reduce dropout, and accelerate recruitment.

Frequently Asked Questions

How much faster can we reach database lock?

According to an estimate, clinical trial sponsors typically achieve database lock 4-6 weeks faster with Legit.Health. This acceleration comes from immediate data availability, 60% fewer queries, and 95%+ first-pass data quality. Combined with 2-3 weeks faster site activation and 3-4 months faster recruitment, the total timeline acceleration is typically 4-6 months, which can translate to $80-120M in additional revenue for blockbuster drugs.

What data quality improvements can we expect?

Legit.Health delivers 85-95% inter-rater reliability (vs 65-75% with manual scoring), 95%+ data completeness (vs 70-80% industry standard), and 77% reduction in image quality issues. This superior data quality increases statistical power by 15-25%, reduces regulatory queries, and significantly strengthens your submission package. The platform's peer-reviewed validation provides the evidence regulators require for accepting AI-generated endpoints.

Does Legit.Health integrate with our EDC system?

Yes, Legit.Health provides seamless integration with major EDC platforms including Medidata Rave, Veeva Vault EDC, Oracle Inform, IQVIA, and REDCap. Our data export formats (CSV, JSON, XML) are configured to match your specific protocol requirements, and we offer both automated and on-demand data transfer schedules. The typical integration setup takes 2-4 weeks.

What validation evidence supports regulatory submissions?

Legit.Health's algorithms are backed by peer-reviewed publications in top-tier journals including JID Innovations, Skin Research & Technology, and JEADV. Our clinical validation studies demonstrate accuracy comparable to expert dermatologists, which strengthens regulatory submissions to FDA, EMA, and other agencies. The platform is CE-marked as a Class IIa medical device and compliant with 21 CFR Part 11.

Can this technology support decentralized clinical trials?

Absolutely. Legit.Health's platform is specifically designed for DCT models, with mobile-first image capture, real-time quality checks (DIQA), patient-friendly interfaces, and remote monitoring capabilities that enable sponsors to conduct hybrid or fully decentralized dermatology trials. This DCT-friendly approach helps reach broader patient populations while maintaining data integrity.

How does this improve patient retention in clinical trials?

By streamlining the patient experience (faster visits, less waiting time), providing engaging mobile interfaces, and reducing the burden on both investigators and patients, sponsors see improved retention rates. The platform can also include gamification elements and automated reminders that boost protocol adherence. Clinical trial sponsors report 15-20% improvement in patient retention to study completion.

What dermatology conditions are supported?

The platform supports automated scoring for 50+ dermatological conditions including psoriasis (PASI), atopic dermatitis (EASI, SCORAD), hidradenitis suppurativa (IHS4, HiSCR), acne (ALEGI), alopecia (SALT), urticaria (UAS), and many others commonly evaluated in clinical trials. Custom scoring algorithms can be developed for novel endpoints.

How long does implementation take for a clinical trial?

Typical implementation timelines range from 2-4 weeks, including protocol customization, EDC integration setup, site training, and user access provisioning. We can accelerate this to 1 week for urgent trial starts. Our dedicated clinical trial manager handles the entire process, minimizing burden on your team.

What is the pricing model for clinical trial sponsors?

Pricing is structured per patient per month or per endpoint assessment, with volume discounts for multi-site trials. We offer flexible models including per-trial licensing, per-patient pricing, and enterprise agreements for sponsors running multiple dermatology trials. Contact our team for a customized quote based on your trial specifications.

Summary

In summary, Legit.Health offers significant advantages for dermatology clinical trials:

• Improved site training efficiency and adherence → fewer missing/incomplete data.
• Reduced investigator burden → increased site participation and retention.
• Objective, standardised severity scoring and image-quality control → higher data quality.
• Enhanced operational efficiency and monitoring transparency → faster timelines, fewer surprises.
• Competitive advantage for site recruitment → access to better dermatology sites.
• Strong scientific / regulatory underpinning via peer-reviewed publications → increased confidence in endpoints.

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References

Footnotes

1. Medela, A., Mac Carthy, T., Aguilar Robles, S. A., Chiesa-Estomba, C. M., & Grimalt, R. (2022). Automatic SCOring of Atopic Dermatitis using deep learning: A pilot study. JID Innovations, 2(3), 100107. https://doi.org/10.1016/j.xjidi.2022.100107 ↩ ↩² ↩³

2. Hernández Montilla, I., Medela, A., Mac Carthy, T., Aguilar, A., Gómez Tejerina, P., Vilas Sueiro, A., González Pérez, A. M., Vergara de la Campa, L., Luna Bastante, L., García Castro, R., & Alfageme Roldán, F. (2023). Automatic International Hidradenitis Suppurativa Severity Score System (AIHS4): A novel tool to assess the severity of hidradenitis suppurativa using artificial intelligence. Skin Research and Technology, 29(6), e13357. https://doi.org/10.1111/srt.13357 ↩ ↩² ↩³ ↩⁴

3. Dagnino, D., Medela, A., Martorell, A., Mac Carthy, T., Aguilar, A., Fernandez, G., Gomez-Tejerina, P., & Roustan-Gullon, G. (2025). Artificial intelligence-based quantification to assess the Automatic Psoriasis Area and Severity Index. JEADV Clinical Practice, 4(1), 70143. https://doi.org/10.1002/jvc2.70143 ↩ ↩² ↩³

4. Hernández Montilla, I., Mac Carthy, T., Aguilar, A., & Medela, A. (2023). Dermatology Image Quality Assessment (DIQA): Artificial intelligence to ensure the clinical utility of images for remote consultations and clinical trials. Journal of the American Academy of Dermatology, 88(4), 927–928. https://doi.org/10.1016/j.jaad.2022.11.002 ↩ ↩²

5. Mac Carthy, T., Hernández Montilla, I., Aguilar, A., García Castro, R., González Pérez, A. M., Vilas Sueiro, A., Vergara de la Campa, L., Alfageme, F., & Medela, A. (2023). Automatic Urticaria Activity Score: Deep learning-based automatic hive counting for urticaria severity assessment. JID Innovations, 4(1), 100218. https://doi.org/10.1016/j.xjidi.2023.100218 ↩

6. Medela, A., Sabater, A., Hernández Montilla, I., Mac Carthy, T., Aguilar, A., & Chiesa-Estomba, C. M. (2025). The utility and reliability of a deep learning algorithm as a diagnosis support tool in head & neck non-melanoma skin malignancies. European Archives of Otorhinolaryngology, 282(3), 1585–1592. https://doi.org/10.1007/s00405-024-08951-z ↩