Pregnancy
How NIPT has evolved and what AI NIPT means in 2026

Article produced in association with London Pregnancy Clinic and Spital Clinic
Non-invasive prenatal testing has been part of antenatal care in the UK since the early 2010s.
In the years since its introduction, the test has undergone significant expansion in terms of what it can detect, how early it can be performed, and how its results are interpreted.
In 2026, NIPT is also beginning to incorporate artificial intelligence at the analysis stage.
This article explains what the test currently involves, what has changed, and what the phrase ‘AI NIPT’ actually refers to in clinical practice.
How Non-Invasive Prenatal Testing Works
From around nine weeks of pregnancy, small fragments of fetal DNA circulate in the maternal bloodstream. These are known as cell-free fetal DNA (cffDNA).
NIPT works by extracting this DNA from a maternal blood sample and analysing it to detect chromosomal differences in the fetus.
Because the test uses a maternal blood draw rather than sampling the placenta or amniotic fluid, it carries no risk of miscarriage.
It is a screening test rather than a diagnostic one, meaning a positive result requires confirmation through a diagnostic procedure such as CVS or amniocentesis.
NICE guidance on non-invasive prenatal testing, published as Diagnostics Guidance DG46, sets out the evidence for its use in detecting the three most common trisomies.
Currently, the NHS does not offer Non-Invasive Prenatal Testing (NIPT) to all pregnant individuals, but rather as a contingent or second-line test for a select group deemed at higher chance of carrying a baby with certain chromosomal conditions
What NIPT Can Now Detect
When NIPT was introduced, tests typically screened for trisomies 21, 18 and 13. Detection capabilities have expanded considerably since then.
Tests available in 2026 can screen for:
- All chromosomal trisomies and some monosomies across the 23 pairs of chromosomes
- Sex chromosome conditions including Turner syndrome (45,X) and Klinefelter syndrome (47,XXY)
- Microdeletions: small missing sections of chromosomes associated with conditions such as DiGeorge syndrome, Angelman syndrome and Prader-Willi syndrome
- Single-gene disorders, where parental carrier status has been established
Tests such as the KNOVA NIPT, for which London Pregnancy Clinic was the first UK provider, are now capable of screening for up to 100 conditions from a single blood draw.
This represents a substantial expansion from the three-trisomy scope of a decade ago.
What Has Changed in 2026
Three developments characterise the current state of NIPT in clinical practice.
First, testing is available earlier, with reliable results from nine weeks and some protocols beginning comprehensive genomic assessment from 10 weeks.
Second, expanded condition panels mean that families can choose the level of detection most appropriate for their situation, from basic trisomy screening to comprehensive genomic analysis.
Third, integrated prenatal pathways are becoming more common, combining NIPT with detailed anatomical scanning and genetics counselling rather than treating the test as a standalone investigation.
What AI NIPT Means in Practice
Artificial intelligence has entered NIPT analysis at the stage where raw cfDNA data is processed and interpreted.
Traditional NIPT analysis uses statistical models to compare the proportions of chromosomal DNA fragments in the maternal sample. AI-enhanced platforms apply machine learning to this process.
A study published in Frontiers in Genetics describes the development of an algorithm using cfDNA fragment distance analysis that improves accuracy by modelling the data in a more nuanced way than conventional statistical approaches.
In clinical practice, the most established AI NIPT platform is Panorama AI NIPT, which applies machine learning to cell-free DNA analysis to improve sensitivity and specificity for common aneuploidies and to extend detection to rarer variants.
The term ‘AI NIPT’ describes this category of platform, not a single product, and it is expected to become standard across major NIPT providers as the underlying technology matures.
The key clinical difference between AI-powered and conventional NIPT is not the type of conditions screened for but the quality of the analysis applied to the same data.
This translates to fewer false positives, fewer uninformative results and greater confidence in a negative finding.
Choosing Between Available Tests
The choice of NIPT should be guided by individual clinical circumstances and pre-test genetic counselling. For families with no known genetic risk factors, standard trisomy screening provides high accuracy at lower cost.
For those with a family history of genetic conditions or who have received an abnormal ultrasound finding, an extended panel or AI-powered test may be appropriate.
The Importance of Genetic Counselling
NIPT is a screening test and, like all screening tests, it produces a probability rather than a certainty. A positive result requires follow-up diagnostic testing before any clinical decisions are made.
A negative result substantially reduces risk but does not eliminate it. Understanding what results mean in both directions requires expert clinical input.
Pre-test counselling ensures that patients understand what they are consenting to; post-test counselling ensures that results are interpreted accurately and next steps are clear.
This is particularly important for expanded panels, where the clinical significance of some findings may be uncertain or variable in presentation.
Disclaimer: This article is produced for informational purposes only and does not constitute medical advice, diagnosis or treatment.
Clinical guidance referenced reflects published NHS, NICE and RCOG standards as at March 2026. Individual circumstances vary; readers are advised to consult a qualified healthcare professional before acting on any information in this article.
This piece was produced in association with London Pregnancy Clinic and Spital Clinic, which provided background clinical information for editorial purposes.
Hyperlinks to external sources are included for reference only and do not represent an endorsement of any product, service or organisation.
Pregnancy
Early birth safer in high blood pressure pregnancies – study
Pregnancy
App tracks heart risk after high-risk pregnancies

A recent study developed a new “digital companion” to support the prevention and follow-up of maternal cardiovascular risk in women with pregnancy complications.
Cardiovascular disease, or CVD, is the leading cause of premature death and illness in women, yet sex-specific causes remain understudied and women are underrepresented in research.
Pregnancy complications, including hypertensive disorders of pregnancy, or HDP, and gestational diabetes mellitus, or GDM, are strong predictors of future CVD, with pregnancy itself acting as a natural stress test.
Despite CVD accounting for 35 per cent of female deaths worldwide in 2019, systematic postpartum prevention remains limited in practice and incidence continues to rise.
Myocardial infarction, commonly known as heart attack, and stroke are the main fatal CVD events in women. Up to one-third of women develop hypertension within a decade after HDP, especially as maternal age rises.
Obstetric guidelines have historically lacked clarity on early CVD prevention after HDP and GDM, often relying on expert consensus rather than evidence.
Some cardiology guidelines now recommend personalised approaches, such as periodic hypertension and diabetes screening. Norwegian guidelines recommend cardiovascular risk evaluation at three months and one year postpartum, but adherence in practice is uncertain.
Effective risk reduction requires intervention before middle age. The immediate postpartum period following HDP or GDM is a critical window for early detection and intervention, offering an opportunity to engage women in cardiovascular health management, particularly as pregnancy can encourage long-term lifestyle awareness.
Electronic health, or eHealth, refers to the use of digital technologies and electronic communication tools to support healthcare services, medical information management and related health activities.
Systematic, eHealth-supported postpartum prevention can improve maternal health literacy and long-term cardiovascular outcomes.
However, there is a significant gap in targeted, eHealth-based postpartum interventions for cardiovascular risk management after HDP and GDM, despite strong patient demand and international calls for coordinated digital health strategies.
Home blood pressure monitoring shows promise, but broader digital support remains limited.
A cardiovascular postpartum follow-up programme was created as a mobile app based on Norwegian and international guidelines.
The MumCare app was developed through co-creation involving users, stakeholders and clinical experts. Five qualitative interviews and 10 user testing sessions informed improvements.
This study primarily analysed the iterative co-creation process used to develop the app, rather than evaluating clinical outcomes.
The MumCare project team in Oslo included an IT expert, obstetricians, a midwife, a GP, two sociologists and two cardiologists, all with relevant experience in eHealth and women’s health. A medical student with technological and medical expertise also helped turn ideas into app features for young women.
User representatives from two national patient associations contributed to information, recruitment, design and testing of the MumCare app.
Both associations provided user perspectives and took part in interviews and app testing. Additional users with HDP or GDM at Oslo University Hospital were also involved throughout the co-creation process.
The app’s digital infrastructure prioritises security and privacy, using encryption, de-identification and two-factor authentication.
User data is stored securely on the app and, for research purposes and with consent, on a dedicated University of Oslo server in line with GDPR and Norwegian regulations.
A linear Stage-Gate model structured the co-creation process, dividing it into phases with quality checkpoints reviewed in project meetings.
This approach balanced internal development with external user feedback, helping ensure the app is evidence-based, technically robust and user-centred.
The MumCare app guides postpartum women through tracking blood pressure, weight, physical activity and lab results, and provides personalised feedback to support self-management, mainly during the first postpartum year.
It also includes educational resources such as videos and guideline-based information to support understanding and engagement.
The app is also designed to support the transition from specialist pregnancy care to long-term follow-up with general practitioners.
It is described as a “digital companion” or health coach and does not replace clinical diagnosis or function as a medical device.
The co-creation process followed four phases focused on technical and procedural development.
In phase 1, input from expert organisations and user representatives established the app’s technical foundation.
It also reminds users of the one-year postpartum follow-up with their GP, a key time to assess risk factors and future care needs.
User organisation representatives gave feedback in phase 1, directly guiding content and feature development.
Phase 2 interviews confirmed that users want to monitor cardiovascular risk factors after HDP and GDM.
The analysis highlighted three themes: self-care strategies and uncertainties about hypertension, the need for accessible health information, and a more personalised approach to blood pressure monitoring in the app.
Concerns were also raised that frequent monitoring or app use could increase stress or create a sense of burden.
In phase 3, the app’s design and features were revised in response to feedback to improve usability and make sure they met users’ needs.
These changes led to a more intuitive and supportive interface for women during and after pregnancy.
Phase 4 involved building a prototype based on the updated designs, followed by further refinements after testing by the project team and users. Initial pilot testing with a small number of users suggested the app met its objectives and functioned as intended.
The MumCare app was co-created with input from experts, user organisations and patients over four phases.
Early expert and organisational contributions helped define the app’s goals, while ongoing feedback from patients helped ensure the design and content reflected users’ real needs.
This collaborative approach resulted in an app tailored to support women with pregnancy complications.
The MumCare app is currently being evaluated in a randomised controlled clinical trial that began in June 2024, with results needed to determine whether it improves long-term cardiovascular outcomes.
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