An Advanced Decision Support Tool, Opt-IVF for Clinical Ivf Practice

NCT05564702 | Completed

• 1 other identifier: SRT-2022-2
• Study Type: interventional
• Target: 93
• Locations: 1 country
• Sites: 1

Brief Summary

Aim: A Clinical trial to determine the effectiveness of using the proposed decision support tool for each patient's customized optimal drug dosage profile. This will be a two-arm clinical trial involving 200 patients; one arm will undergo superovulation using dosages predicted by the decision support tool while the other arm will undergo current standard treatment. The investigators will compare the outcomes of the two groups of patients in terms of the numbers and percentage of mature follicles retrieved at the end of each cycle, total FSH and HMG dosages used, and the number of required testing days for that cycle. The patients considered will include all ages, with and without PCOS, and low, average, and high responders.

Conditions

Infertility

Keywords

IVF; Opt-IVF

Outcome Measures

Primary Outcomes (6)

• Total per cycle dosage

  Average dosage per cycle

  At the end of cycle 1 (each cycle is 17 days)

• Number of Ultrasounds

  average number of ultrasounds per cycle

  At the end of cycle 1 (each cycle is 17 days)

• Number of mature oocytes retrieved

  average oocytes retrieved

  At the end of cycle 1 (each cycle is 17 days)

• Number of Metaphase 2 follicles

  average number of M2s obtained per cycle

  At the end of cycle 1 (each cycle is 17 days)

• Number of Embryos

  average number of Embryos per cycle

  At the end of cycle 1 (each cycle is 17 days)

• Number of Grade A embryos

  average number of grade A embryos per cycle

  At the end of cycle 1 (each cycle is 17 days)

Secondary Outcomes (1)

• Pregnancy rate

  0-3 months

Study Arms (2)

Opt-IVF predicted drug dosage

EXPERIMENTAL

In this arm, OPT-IVF will use the patient's age and day three serum day AMH and AFC levels to decide the starting dose for the patient's cycle. It will also use the first day and day 5 data collected (Follicular size distribution, estrogen levels) for that patient to determine the optimal dosage profile for the entire cycle for that patient. The dosage predicted by Opt-IVF will be used for the patient in this arm.

Other: Opt-IVF predicted dosage

Traditional drug treatment

ACTIVE COMPARATOR

The current practice of Physician specified dosage will be used in this arm.

Other: traditional drug treatment

Interventions

traditional drug treatment OTHER

The patients in this arm will be given doctor specified dosage.

Traditional drug treatment

Opt-IVF predicted dosage OTHER

The patients in this arm will be given dosage predicted by Opt-IVF.

Opt-IVF predicted drug dosage

Eligibility Criteria

• Age: 18 Years - 50 Years
• Gender Eligibility Details: This treatment is given to women only
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64)

You may qualify if:

• women between 18 to 50 years of age

You may not qualify if:

• men and children

Sponsors & Collaborators

• Stochastic Research Technologies LLC: lead
• Akansha Hospital and Research Institute, India: collaborator

Study Sites (1)

Akansha Hospital and Research Institute

Anand, Gujarat, 388001, India

Location

Related Publications (4)

• Yenkie KM, Diwekar U. Uncertainty in clinical data and stochastic model for in vitro fertilization. J Theor Biol. 2015 Feb 21;367:76-85. doi: 10.1016/j.jtbi.2014.11.004. Epub 2014 Dec 4.

  PMID: 25484007 BACKGROUND

• Diwekar U, Patel N, Patel N, Patel M, Bhadarka H, Ghoghari P, et al.(2022). A Non-Randomized Clinical Trial of a Decision Support Tool to Optimize Superovulation Cycles in Individual Patients. J Fertil In vitro IVF World w Reprod Med Genet Stem Cell Biol. 10:261.

  BACKGROUND

• Nisal A, Diwekar U, Bhalerao V. Personalized medicine for in vitro fertilization procedure using modeling and optimal control. J Theor Biol. 2020 Feb 21;487:110105. doi: 10.1016/j.jtbi.2019.110105. Epub 2019 Dec 3.

  PMID: 31809718 BACKGROUND

• Yenkie KM, Diwekar UM, Bhalerao V. Modeling the superovulation stage in in vitro fertilization. IEEE Trans Biomed Eng. 2013 Nov;60(11):3003-8. doi: 10.1109/TBME.2012.2227742. Epub 2012 Nov 15.

  PMID: 23193444 RESULT

MeSH Terms

Conditions

Infertility

Condition Hierarchy (Ancestors)

Genital Diseases; Urogenital Diseases

Study Officials

• Urmila Diwekar

  Stochastic Research Technologies LLC

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: TRIPLE
• Who Masked: PARTICIPANT, INVESTIGATOR, OUTCOMES ASSESSOR
• Masking Details: Only care provider Dr. Patel will know the identity of each patient.
• Purpose: TREATMENT
• Intervention Model: SEQUENTIAL
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Model Details: This will be randomized study of patients undergoing IVF treatment. The treatment given to one arm will be based on Opt-IVF decision support tool and standard doctor specified treatment with other arm.

Study Record Dates

• First Submitted: September 26, 2022
• First Posted: October 3, 2022
• Study Start: October 8, 2022
• Primary Completion: March 15, 2023
• Study Completion: March 15, 2023
• Last Updated: April 28, 2023

Record last verified: 2023-04

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, CSR
• Time Frame: one month after the study is completed
• Access Criteria: Via email

Locations

IN (1)