The Securities and Exchange Commission today announced that Cicely LaMothe, Deputy Director of the Division of Corporation Finance, has retired from the agency.
“Cicely has gone above and beyond the call of duty over the past twenty-four years to serve the public in her many critical roles in the Division of Corporation Finance,” said Jim Moloney, Director of the Division of Corporation Finance. “Throughout her tenure she has contributed her passion, commitment, and accounting expertise to support our mission – to ensure investors have the information they need to make informed decisions. She will be sorely missed, and we wish her all the best on her next chapter.”
Ms. LaMothe joined the Division of Corporation Finance in 2002 and has served in multiple senior leadership positions, including Program Director of the Disclosure Review Program, Associate Director of the Office of Assessment and Continuous Improvement, and Associate Director of Disclosure Operations before being named Deputy Director for Disclosure Operations in 2022. She served as Acting Director until Jim Moloney was appointed Director on September 30, 2025.
During Cicely’s tenure she:
Increased regulatory transparency through the issuance of external guidance, including 25+ new and updated Compliance and Disclosure Interpretations (covering clawbacks, deSPACs, Rule 10b5-1, etc.), Staff Legal Bulletin 14M clarifying views on the application of Rule 14a-8, and seven CF Staff Statements on rapidly evolving crypto-related matters (liquid staking, stablecoins, mining activities, meme coins, crypto ETPs).
Drove policy recommendations to the Commission regarding the acceleration of registration statements with mandatory arbitration provisions as well as Concept Releases covering both Foreign Private Issuers and Asset-Backed Securities.
Expanded accommodations for companies submitting draft registration statements to promote capital formation.
Advanced key improvements in the division’s approach on the reviews of public company disclosures that modernize and enhance the efficiency and effectiveness of regulatory oversight.
“After more than two decades at the SEC, I depart with a deep sense of honor and gratitude for the opportunity to serve the American public. The work has been incredibly challenging and rewarding, and I have learned immensely from the dedicated individuals who commit themselves daily to this critical mission. To my colleagues, your integrity and, more importantly, your friendship, has been my true inspiration and constant motivation,” said Ms. LaMothe.
Before coming to the SEC, Ms. LaMothe worked for six years in the private sector, including as the financial reporting manager for a public company and with a national accounting firm. Ms. LaMothe earned her bachelor’s degree in accounting from Hampton University and is a licensed Certified Public Accountant.
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Silver prices tumbled on Monday, dragging down gold and other precious metals, as a record-breaking rally went abruptly into reverse.
Spot silver prices fell 9 per cent by late-afternoon trading to just under $72 a troy ounce, on track for their biggest one-day fall since the Covid pandemic, reversing the gains it had made during the thinly traded Boxing Day session.
The decline spilled over into gold, which slid more than 4 per cent to just above $4,300, dragging it down from the string of record highs it had reached in recent sessions.
Traders said the move reflected both profit-taking after a strong run, and a reaction to a notice issued by CME on December 26 indicating that margin requirements for a range of metal futures contracts, including silver and gold, are set to rise after the close on December 29. The higher margins raise the cost of holding leveraged positions, prompting some traders to pare back exposure.
Rushabh Amin, a multi-asset portfolio manager at Allspring Global Investments, said a combination of the higher margin requirements, thin liquidity, and other factors were “working against not just silver but bleeding into other precious metals”.
“This is not a blow-off top, per se, but a very strong consolidation,” he added, referring to a market term for a steep drop that follows a speculative surge.
The sell-off followed a record rally in the metal, as investors moved into haven assets as a refuge against geopolitical tensions and worries over the debasement of traditional currencies such as the US dollar. Spot prices breached $80 per ounce for the first time in early trading on Monday, from $50 as recently as November.
Analysts have seen signs of a speculative bubble in precious metals, as a rush of investor interest comes into asset classes with a constrained level of supply. The metals have also been boosted by US interest rate cuts that have sapped the relative attractiveness of dollar assets.
Ole Hansen, head of commodity strategy at Saxo Bank, said silver’s rally had become “parabolic”, leaving the market vulnerable as margin requirements, while rising, remained low by historical standards.
In a sign of growing attention on silver’s surge, Elon Musk wrote on X on December 26 that higher prices were “not good”, citing the metal’s widespread industrial use.
In a December 29 note, UBS said gold’s surge had been driven in part by “seasonal liquidity” and demand for real assets, warning that prices were trading at an “elevated premium” after the metal’s strongest year since 1979.
China’s State Council has issued the Tariff Adjustment Plan for 2026, updating import and export tariffs on a range of goods and adding new tariff lines to the schedule. The 2026 plan focuses on the development of key industries, in particular those related to high-end technology, the green transition, and healthcare, while upholding the country’s commitments under existing free trade agreements.
The State Council Tariff Commission (SCTC) has released the updated tariff schedule for 2026, implementing new provisional tariff reductions and adjusting tariff lines in efforts to boost development in focus industries and support domestic provision of key services.
The 2026 tariff schedule includes tariff reductions on critical components and materials related to advanced and emerging technologies, renewable energy, and healthcare in particular. Meanwhile, most-favored nation (MFN) tariffs for certain imports previously granted tariff reductions have been restored in response to changing supply and demand in domestic industries.
The new tariff schedule will be implemented from January 1, 2026.
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Overview of China’s 2026 Tariff Adjustment Plan
Tariff schedule adjustments: In 2026, China’s tariff schedule covers 8,972 product categories, 12 more than in 2025.
Provisional import tariff rates: From January 1, 2026, 935 product categories will be subject to provisional import tariffs that are lower than most favored nation (MFN) rates.
Tariff reductions: In 2026, China will continue to lower tariff rates on goods entering the country to support the development of new quality productive forces, enhance people’s livelihoods, expand high-level opening up, and promote high-quality development.
Tariff increase: From January 1, 2026, import tariffs on some commodities will be raised to enhance the productivity of domestic industries in response to changes in domestic supply and demand. Examples include micro motors, printing machines, and sulfuric acid.
Conventional tariff rates: Conventional tariff rates will be applied to imported goods originating from 34 countries or regions covered by China’s 24 free trade agreements (FTAs) and preferential trade arrangements.
Preferential tariff treatment: China will continue to grant zero-tariff treatment to 43 least-developed countries with which it has established diplomatic relations. At the same time, preferential tariffs will continue to be applied to some imported goods originating in Bangladesh, Laos, Cambodia, and Myanmar.
Tariff structure updates: To serve scientific and technological progress, the development of the circular economy, and the development of the under-forest economy, new tariff lines and descriptions have been added to the tariff schedule.
Tariff quota: Tariff quota management will continue to be implemented on eight categories of commodities: wheat, corn, rice, sugar, wool, wool top, cotton, and fertilizer. Tax rates on these commodities remain unchanged.
Export tariffs: Export tariffs will continue to be imposed on 107 commodities, including ferrochrome, 68 of which are subject to provisional export tariff rates.
Tariff adjustments in 2026
Tariff reductions
In 2026, China will implement provisional tariff reductions on 935 categories of goods, with new tariff adjustments made to “enhance the synergy between domestic and international markets and resources, and to expand the supply of high-quality goods”. The reductions particularly seek to benefit the development of innovative and emerging technologies – the “new quality productive forces” – and to improve the quality of life in China, in particular by lowering the cost of access to high-quality healthcare services.
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As such, many of the new tariff reductions target key components for emerging technologies, with tariffs reduced on products for use in advanced materials, aviation, lithium-ion batteries, renewable energy, and semiconductors, including CNC hydraulic air cushions, carbon fiber prepreg, recycled black powder, and unroasted pyrite.
Additionally, tariffs have been reduced on a range of healthcare products, including artificial blood vessels, formulated diagnostic kits for sexually transmitted diseases, and angular contact ball bearings for medical devices, among others.
Tariff increases
Starting January 1, 2026, China will also restore MFN rates on certain products that previously enjoyed reduced tariffs, in order to enhance the productivity of domestic industries based on changes in domestic industrial development and supply and demand. These include restoring the MFN rates for imports of commodities such as micro motors, printing machines, and sulfuric acid.
Tariff reductions under FTAs
Special tariff rates negotiated through FTAs will continue to be applied to certain imported goods originating from the 34 trading partners that are covered by China’s 24 FTAs and preferential trade arrangements.
Further tariff reductions will be implemented in accordance with the FTAs between China and the following countries:
New Zealand
Peru
Switzerland
South Korea
Australia
Pakistan
Mauritius
Cambodia
Nicaragua
Ecuador
Serbia
The Maldives
The Regional Comprehensive Economic Partnership (RCEP)
Additionally, existing preferential tariff rates will continue to be applied to relevant imported goods, including rates implemented under:
The FTAs between China and ASEAN, Chile, Singapore, Georgia, Iceland, and Costa Rica;
The early harvest arrangement of the FTA between China and Honduras;
The Closer Economic Partnership Arrangement (CEPA) between the Mainland and Hong Kong and Macao;
The Cross-Strait Economic Cooperation Framework Agreement (ECFA); and
The Asia-Pacific Trade Agreement.
Addition of new tariff items
The number of tariff lines will be increased from 8,960 in 2025 to 8,972 in 2026, with additions serving to enhance scientific and technological development and support the development of the circular economy and under-forest economy. The new additions include intelligent biomimetic robots (as well as other robots), bio-aviation kerosene, and under-forest ginseng.
In addition to the new tariff items, updated descriptions have been provided for wild ginseng, forest ginseng, biodiesels, and intelligent bionic robots.
Understanding the China’s 2026 tariff schedule
Bolstering technological self-reliance
The SCTC states that one of the intents of the tariff reductions is to “promote high-level technological self-reliance and the construction of a modern industrial system”, reflecting China’s ongoing efforts to bolster self-reliance in core technologies, such as semiconductors, as well as modernize and move its traditional industries up the value chain.
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The new tariff schedule therefore temporarily reduces tariffs on goods that are essential for the production of advanced materials, such as CNC hydraulic air cushions for presses, for which the tariff has been reduced from 12 percent to 6 percent, and irregularly shaped composite contact strips, for which the tariff will be lowered from 8 percent to 5 percent. Additionally, duties on carbon fiber prepregs for use in aircraft have been lowered from 17 to just 5 percent, in an effort to enhance the competitiveness of China’s aircraft construction industry.
Tariff reductions also extend to specialised equipment used in semiconductor manufacturing, including constant temperature and humidity control devices for coating and developing machines. By lowering import costs for such equipment, the authorities aim to ease constraints in upstream manufacturing processes while domestic capabilities continue to be developed.
The tariff reductions thereby seek to enhance the development of key industries in which China is seeking to bolster its competitiveness and self-reliance, notably aircraft building and semiconductors, two strategically important areas in which it is still reliant on imports.
Supporting the green transition
The second target of the tariff reductions according to the SCTC is to support the “comprehensive green transformation of economic and social development”. As such, tariffs on resource-based commodities that are essential for the production of batteries, namely recycled black powder for use in lithium-ion batteries (for which the tariff has been reduced from 6.5 percent to 3 percent) and unroasted pyrite (further reduced from 1 percent in 2025 to 0 percent in 2026). Tariff reductions for a range of other battery materials and components remain in place from previous years.
China is massively expanding its renewable energy capacity and output, with plans to continue this expansion in the years to come under its dual carbon targets and its carbon reduction commitments set out in its Nationally Determined Contributions (NDCs) announced in September 2025. In its NDCs, China has targeted to increase the installed capacity of wind and solar power generation to six times its 2020 levels by 2035, while striving to reach 3,600 GW. Additionally, it aims to make electric vehicles the “main driver” of new vehicle purchases.
Meeting these targets will require sustained, large-scale investment across the clean-energy value chain, particularly in battery manufacturing and energy storage. By lowering tariffs on key upstream inputs, China is seeking to reduce production costs, mitigate supply bottlenecks, and support the domestic scaling of strategic green industries, while also maintaining access to global supply chains at a time of heightened international competition in clean-tech manufacturing.
Improving healthcare provisions
Continuing one of the priorities set out in the 2025 tariff adjustment schedule, China will further reduce tariffs on selected medical equipment and healthcare-related materials in an effort to improve healthcare standards and overall quality of life. The latest reductions focus on both advanced medical devices and diagnostic inputs, reflecting an emphasis on improving access to high-quality treatment and disease detection.
Key tariff cuts include artificial blood vessels, for which tariffs have been reduced from 4 percent to 2 percent, as well as pre-prepared diagnostic reagent kits used to detect hepatitis A, B and C viruses, HIV, and Treponema pallidum (syphilis), which will see tariffs fall from 3 percent to zero. In addition, tariffs on specialised angular contact ball bearings for medical equipment have been halved from 8 percent to 4 percent.
These reductions signal a continued policy focus on lowering the cost of advanced medical technologies and critical diagnostics, supporting both healthcare providers and patients. They also underline China’s broader objective of upgrading its healthcare system through improved access to high-end imported components and materials, while complementing domestic efforts to move up the medical manufacturing value chain.
Significance of the addition of new tariff lines
Beyond adjustments to existing tariff rates, the additions of new tariff lines also closely align with China’s evolving industrial and development priorities, particularly in advanced technologies, the circular economy, and rural economic revitalization.
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For instance, the addition of wild and under-forest ginseng underscores a policy priority that has been increasingly emphasized as part of China’s broader rural revitalization strategy. Developing the under-forest economy, which encompasses economic activities conducted beneath forest canopies, such as the cultivation of medicinal herbs and specialty agricultural products, was explicitly highlighted in the recommendations for the 15th Five-Year Plan. The new additions therefore reflect efforts to standardise classifications, improve regulatory oversight, and support the scaling and commercialization of high-value forest-based products (under-forest ginseng will now be subject to a 20 percent MFN tariff). This, in turn, aligns with broader objectives to raise rural incomes, improve land-use efficiency, and promote more sustainable models of agricultural development.
The inclusion of bio-aviation kerosene, as well as other aviation kerosene, suggests an effort to better differentiate fuels within the tariff framework and to accommodate the development and use of alternative and lower-carbon aviation fuels. This reflects China’s longer-term ambitions to reduce emissions in hard-to-abate sectors such as aviation, while supporting the development of more resource-efficient and sustainable energy pathways.
Finally, the addition of tariff lines for intelligent biomimetic robots underscores China’s ambitions in emerging and advanced technologies. Robotics has been identified as a key component of China’s push to develop new quality productive forces, with applications spanning manufacturing, healthcare, logistics, and environmental monitoring. By explicitly recognizing intelligent biomimetic robots within the tariff schedule and refining the definitions for intelligent bionic robots, China is signalling a desire to better accommodate technological advances and support domestic innovation and industrial upgrading.
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3M to debut AI-powered assistant ‘Ask 3M’ and expanded 3M Digital Materials Hub at CES 2026
New generative tool and capabilities can accelerate customer-centric innovation, enable creation of previously nonexistent materials
ST. PAUL, Minn., Dec. 29, 2025 /PRNewswire/ — 3M (NYSE: MMM) today announced two digital innovations that will accelerate customer design workflows:
Ask 3M, a new AI-powered digital assistant that helps customers find solutions to design challenges using 3M’s vast portfolio of adhesives and tapes
An expanded3M Digital Materials Hub, which enables direct collaboration with 3M scientists through the Workbench feature and powers virtual materials sampling for generative solutions that don’t yet exist
To speed the introduction of solutions for 3M customers, these tools leverage generative AI, advanced modeling, and simulation-ready data cards, empowering users to design and digitally validate materials before investing in physical prototypes.
“At 3M, we’re combining decades of material science with AI so engineers can make better decisions, faster,” said Holly Semerad, chief marketing officer for 3M’s Safety & Industrial Business Group. “Together, Ask 3M and the 3M Digital Materials Hub allow customers of varying scope and scale to move from design challenge to solution concept then digital selection and simulation in minutes. We can further accelerate the testing timeframe with small quantity purchase options for final and confident prototyping.”
At launch, Ask 3M will be piloted to engineers solving bonding design challenges utilizing tapes and adhesives—largely within 3M’s Safety & Industrial Business Group. Leveraging Amazon Web Services’ (AWS) secure and scalable AI capabilities, including Amazon Bedrock and AgentCore, Ask 3M and the 3M Digital Materials Hub demonstrate how agentic AI and advanced simulation can help 3M customers accelerate innovation cycles, reduce prototyping costs, and bring better products to market faster. Powered by AWS, the AI assistant guides users through substrates, environmental conditions, assembly methods, and performance targets to recommend suitable options, helping teams move from problem to product-fit more quickly.
The expanded 3M Digital Materials Hub, which launched in early 2025, will now include Optical Models, which represent 3M optical film performance for use in common simulation environments. Engineers in automotive, consumer electronics, and advanced manufacturing can quickly assess optical behaviors and material tradeoffs earlier in the process, reducing iterations and enabling faster decision-making. In a pilot with select customers, engineers reported that the tool enables seamless use of 3M materials into virtual simulations, accelerating prototyping and design.
In addition to these capabilities, the expanded platform also enables customers to request bespoke virtual materials—ones that solve their specific design challenges but don’t yet exist. It does this by leveraging 3M’s decades of material science and engineering expertise, which means the path to create these unique solutions is already in place and 3M can accelerate their development and delivery.
“With these platforms, 3M is redefining how engineers discover, evaluate, and simulate materials,” said Jason Langfield, 3M Digital Materials Hub project lead. “By drawing on 3M’s deep technological and application expertise, we can deliver secure, scalable access to mechanical models, optical models and virtual materials, while helping our customers reduce iterations, accelerate decisions, and bring better solutions to market faster.”
3M will showcase these solutions as part of its exhibition at CES 2026, located at Booth #8505 in the North Hall of the Las Vegas Convention Center. To learn more, or to schedule a meeting at CES, please email CES-3M@mmm.com.
For more information on 3M’s presence at CES, visit https://news.3m.com/CES.
About 3M 3M (NYSE: MMM) is focused on transforming industries around the world by applying science and creating innovative, customer-focused solutions. Our multi-disciplinary team is working to solve tough customer problems by leveraging diverse technology platforms, differentiated capabilities, global footprint, and operational excellence. Discover how 3M is shaping the future at 3M.com/news.
Silver and gold futures are falling sharply after the Chicago Mercantile Exchange, one of the world’s largest trading floors for commodities, required traders to put up more cash to invest in precious metals
NEW YORK — Silver and gold futures fell sharply Monday after the Chicago Mercantile Exchange, one of the world’s largest trading floors for commodities, asked traders to put up more cash to make bets on precious metals with prices surging this year.
This year, gold futures are up 65% and silver has more than doubled.
The CME raised margin requirements for gold, silver and other metals in a notice posted to the exchange’s website Friday. These notices require traders to put up more cash on their bets in order to insure against the possibility that the trader will default when they take delivery of the contract.
Exchanges sometimes boost margin requirements when a commodity or other security goes on a significant run. In its notice, the CME said it was raising margin requirements “per the normal review of market volatility.”
Silver futures tumbled 8% early Monday while gold slid 5%
Silver prices have skyrocketed this year, topping records dating back to the early 1980s when traders tried and failed to corner the silver market. Supplies have dwindled, with production at major mines slowing. At the same time there’s been an increased industrial need for silver for solar panels as well as data centers.
Silver futures were roughly $30 an ounce at the beginning of 2025, and briefly touched $80 an ounce before the CME’s announcement.
Gold futures have risen due in part to geopolitical uncertainty and fears that a bubble is forming in some stock markets. Silver is sometimes referred to among investors as the “poor man’s gold” because it trades in similar patterns as gold for a fraction of the price. But unlike gold, silver has more industrial applications so it tends to more volatile and more exposed to economic cycles.
Disclaimer: Early release articles are not considered as final versions. Any changes will be reflected in the online version in the month the article is officially released.
Author affiliation: Centers for Disease Control and Prevention, Atlanta, Georgia, USA (E.V. Kurbatova, W.C. Whitworth, K.E. Bryant, M.G. Dixon, N.A. Scott, R. Boyd, N.E. Brown, K.N. Chapman Hedges, W. Carr, L.P Peddareddy); Vanderbilt University Medical Center, Nashville, Tennessee, USA (K.E. Dooley); Uganda–Case Western Reserve University Research Collaboration, Kampala, Uganda (G. Muzanyi); University of Cape Town Lung Institute, Cape Town, South Africa (R. Dawson); University of the Witwatersrand Perinatal HIV Research Unit, Johannesburg, South Africa (Z. Waja, N. Martinson); Weill Cornell Medical College, New York, New York, USA (J.S.V. Mathad); University of California Center for Tuberculosis, San Francisco, California, USA (P. Nahid, P.P.J. Phillips); University of Nebraska Medical Center, Omaha, Nebraska, USA (S. Swindells); Johns Hopkins University School of Medicine, Baltimore, Maryland, USA (R.E. Chaisson); Medical University of South Carolina, Charleston, South Carolina, USA (S.E. Dorman)
Globally, among pregnant women in 2011, an estimated 216,000 had concurrent active tuberculosis (TB) (1). Untreated TB during pregnancy can cause pregnancy complications, nonobstetric maternal death, and infant death (2–8). Even if treated, TB during pregnancy poses challenges. For treatment of drug-susceptible pulmonary TB, standard treatment regimens containing isoniazid, rifampin, pyrazinamide, and ethambutol are highly efficacious in nonpregnant women, but well-controlled studies in pregnant women are lacking. More generally, data regarding safety, tolerability, and pharmacokinetics of TB drugs during pregnancy have not been collected or reported systematically, leading to inconsistencies in national and international treatment guidelines (9). For example, international guidelines recommend the use of pyrazinamide during pregnancy in first-line regimens for drug-susceptible TB (10), but US guidelines suggest evaluating the risks and benefits of prescribing pyrazinamide on a case-by-case basis (11). The scarcity of high-quality evidence combined with the worldwide occurrence of >200,000 annual cases of active TB disease among pregnant women highlights the need for additional research in this area to expand treatment options for mothers and protect the health of their infants (9). A February 2024 consensus statement strongly supports the participation of pregnant women in TB research (12), a statement that has been endorsed by community groups (13).
Tuberculosis Trials Consortium Study 31/AIDS Clinical Trials Group A5349 (S31/A5349) was a multicenter randomized controlled phase 3 noninferiority open-label trial that examined two 4-month treatment-shortening rifapentine-containing regimens compared with the standard 6-month control regimen for treatment of drug-susceptible pulmonary TB in nonpregnant participants >12 years of age (14). One investigational regimen contained rifapentine, moxifloxacin, and isoniazid administered for 4 months plus pyrazinamide administered during the first 2 months (rifapentine/moxifloxacin regimen). The other investigational regimen contained rifapentine plus isoniazid administered for 4 months plus pyrazinamide and ethambutol administered during the first 2 months (rifapentine regimen). The trial demonstrated that the 4-month rifapentine/moxifloxacin regimen had efficacy that was noninferior to that of the control and was safe and well-tolerated. The rifapentine regimen did not meet the noninferiority criteria for efficacy (14). The World Health Organization and the US Centers for Disease Control and Prevention (CDC) now recommend the 4-month rifapentine/moxifloxacin regimen for treatment of drug-susceptible TB in nonpregnant patients >12 years of age (15,16). The regimen is not recommended in pregnant women because they were not included in enrollment for the S31/A5349 study.
Although pregnant women were not eligible for enrollment in S31/A5349, some participants became pregnant during their participation in the study, some during study treatment, and some in the follow-up period. We conducted a secondary data analysis to describe pregnancy outcomes and safety among S31/A5349 study participants who became pregnant during the trial.
Study Design
Full details of the S31/A5349 study design, eligibility criteria, enrollment and randomization, safety monitoring, and study outcomes have been published previously (14,17). Pregnant or breastfeeding women were not eligible for enrollment because of uncertainties about the safety of rifapentine, moxifloxacin, and pyrazinamide in those groups (14,17). We required negative urine or serum pregnancy test results for all women of childbearing potential who were not surgically sterilized or who did not meet the study definition of postmenopausal at or within 7 days before screening. Participants of childbearing potential who were not surgically sterilized had to agree to practice an adequate method of contraception (barrier method or nonhormonal intrauterine device) or abstain from sexual activity that can lead to pregnancy during study treatment, regardless of the study regimen (17). Pregnancy tests during study follow-up were not required by the study protocol. We asked participants of childbearing potential during study visits about their last menstrual period, and a pregnancy test could be conducted at the discretion of clinician investigators.
Analysis of Population, Procedures, and Definitions
We included in this secondary analysis all women who were randomized in S31/A5349, took >1 dose of assigned treatment, and became pregnant during participation in the trial. We defined a participant of childbearing potential as a woman 15–49 years of age (18).
For participants who reported pregnancy or were determined to be pregnant while receiving study therapy, including participants in the control arm, we permanently stopped their study treatment (regardless of assigned regimen) and treated their TB according to their respective national TB program or local guidelines (local standard of care). Pregnant participants continued to receive scheduled study follow-up except for study-specific chest radiographs (14,17). Those participants were followed by the site until the pregnancy outcome was known. We did not collect nonstudy TB treatment outcomes in this study.
We advised sites to make efforts to estimate a true conception date to the best of their ability and provided sites with guidance on using and prioritizing information available for the estimation of the conception date to determine if conception took place during study treatment and the fetus had been exposed to study drugs (19) (Appendix). We considered the participant to be exposed to a study drug during pregnancy if the estimated date of conception (EDC) was on or before the last study dose date. Each pregnancy report was reviewed in real-time by the safety officer (possessing an MD degree) at the Clinical Research Branch, Division of Tuberculosis Elimination, at CDC’s National Center for HIV, Viral Hepatitis, STD, and Tuberculosis Prevention.
Sites reported pregnancies on an adverse event (AE) case report form. The form included an EDC as the adverse event onset date. We captured pregnancy outcomes on an AE follow-up case report form and included live birth, fetal death (pregnancy loss at >20 weeks of gestation), spontaneous abortion (pregnancy loss at <20 weeks of gestation), or elective abortion. We defined adverse pregnancy outcomes as fetal loss (fetal death or spontaneous abortion) or infants with a congenital anomaly.
The primary efficacy outcome in the parent trial was TB disease-free survival 12 months after randomization. For each participant, we assigned a primary efficacy outcome status of favorable, unfavorable, or not assessable, as described previously; we further classified unfavorable outcomes as TB-related or not TB-related (14,17). We considered participants with unfavorable and not assessable outcomes to have a not favorable outcome.
The primary safety outcome in the parent trial was the proportion of participants with grade >3 AEs during treatment (with onset up to 14 days after the last dose of study medication). Severity of AEs was graded by the site investigators according to the National Cancer Institute common terminology criteria for adverse events version 4.03 (20), which requires classification of pregnancy as an AE with a grade of >3; therefore, every participant who became pregnant had >1 AE that was grade >3. We excluded the pregnancy AEs from the analysis of safety outcomes. Tolerability was a secondary safety outcome, which we defined as premature discontinuation of the assigned regimen for any reason other than microbiologic ineligibility.
The trial was approved by CDC’s Institutional Review Board and by local ethics committees, and all participants provided written informed consent. The study data were monitored by the Data Safety Monitoring Board.
Data Analysis
We calculated length of exposure to the study drugs as the number of days between EDC and the date of the last study dose. We report frequency of pregnancy outcomes (live birth, fetal loss [death or spontaneous abortion], or elective abortion) among pregnant participants exposed to the study drugs (exposed pregnancies) in the 2 investigational arms compared with the control arm and among participants who became pregnant after study treatment was completed (unexposed pregnancies). We calculated unadjusted risk difference for fetal loss and congenital anomaly comparing investigational regimens to control with exact 95% CIs based on the 2-sided score test. We used SAS 9.4 for those calculations (21). We describe study TB treatment outcomes and AEs experienced by pregnant participants.
We enrolled a total of 740 female participants in S31/A5349 during January 25, 2016–October 30, 2018 (we completed study follow-up in July 2020); 97 (13.1%) of those 740 participants became pregnant during study treatment or follow-up. Five (5%) of those 97 participants became pregnant twice during trial participation, resulting in a total of 102 pregnancies. Of 102 pregnancies, 30 (29.4%) were exposed to the study drugs (either investigational or control arms). Median age of those 30 participants was 24 years (range 18–35 years); 1 participant was living with HIV (Table 1).
Among 30 pregnancies considered exposed, the median number of days of study drug exposure was 39 days (range 11–103 days) in the control regimen, 36 days (range 13–119 days) in the rifapentine/moxifloxacin regimen, and 39 days (range 16–114 days) in the rifapentine regimen. Outcomes of 30 exposed pregnancies were 21 (70%) live births, 5 (16.7%) fetal loss (fetal death or spontaneous abortion), and 4 (13.3%) elected abortions. Fetal loss was reported for 3/13 (23.1%) pregnancies in the control regimen, 1/9 (11.1%) pregnancies in the rifapentine/moxifloxacin regimen, and 1/8 (12.5%) pregnancies in the rifapentine regimen (unadjusted risk difference [RD] −12.0% [95% CI −43.8% to 27.7%] for rifapentine/moxifloxacin vs. control arm; unadjusted RD −10.6% [95% CI −42.7% to 29.8%] for rifapentine vs. control arm) (Table 2). Four of 5 fetal losses occurred in pregnancies of <20 weeks’ gestational age. Among 21 live births in exposed pregnancies (7 in each arm), 1 infant (overall 4.8% of live births) with a congenital anomaly was reported in the rifapentine arm (1/7 live births) (unadjusted RD 14.3% [95% CI −26.0% to 53.3%] for rifapentine vs. control). That infant had congenital musculoskeletal disorder, including clubfeet and myopathy (Table 3).
Of 72 pregnancies considered unexposed, fetal loss was reported in 1/24 (4.2%) pregnancies in the control regimen, 1/26 (3.8%) pregnancies in the rifapentine/moxifloxacin regimen, and 4/22 (18.2%) pregnancies in the rifapentine regimen. One infant with a congenital anomaly was reported in the rifapentine/moxifloxacin regimen (1/20 live births [5.0%]). That infant had congenital umbilical hernia and right inguinal hernia (Table 3).
Among 29 participants with exposed pregnancies in the microbiologically eligible analysis population, study treatment outcome was assigned as unfavorable for 7/13 (53.8%) participants in the control regimen, 4/9 (44.4%) participants in the rifapentine/moxifloxacin regimen, and 3/7 (42.9%) participants in the rifapentine regimen (Table 4). All 14 unfavorable outcomes in this population were in the not assessable category (all were withdrawn from study treatment because of pregnancy).
Of 30 participants with exposed pregnancies included in the safety analysis population, 5/30 (16.7%) experienced grade >3 AEs (excluding pregnancy itself, which was always reported as an AE) during study treatment: 2/13 (15.4%) in the control regimen, 3/9 (33.3%) in the rifapentine/moxifloxacin regimen, and 0/8 (0%) in the rifapentine regimen (Table 5; Appendix Table). No deaths occurred among participants in the study who became pregnant.
This analysis examined pregnancy outcomes among women who became pregnant during participation in the S31/A5349 trial of treatment of drug-susceptible pulmonary TB. We observed no excess fetal losses among pregnant participants in the rifapentine/moxifloxacin arm compared with the control arm, although the numbers were small. We noted no infants with congenital anomalies among those considered exposed to study drugs during pregnancy in the rifapentine/moxifloxacin arm. The overall percentages of fetal loss (16.7%) and congenital anomalies (4.8% of live births) in pregnancies exposed to the study drugs we observed in this trial were similar to those estimated for the United States (19.7% for fetal loss and 3% of live births for congenital anomalies) (22,23).
Because multiple antibiotics are used concomitantly during TB treatment, isolating the effects of individual drugs on pregnancy outcomes is challenging. With regard to rifapentine use in pregnant animals, previous developmental toxicity studies in rats and rabbits suggested that rifapentine produced fetal harm and was teratogenic (24). This description is similar to that of rifampin, which was teratogenic in high doses in animal models (25); however, on the basis of extensive use and years of clinical experience, the use of rifampin to treat TB during pregnancy has benefits greater than safety concerns with respect to curing TB. Studies of rifapentine during human pregnancy and lactation have been limited. In 6 patients randomized to rifapentine for initial treatment of TB in humans and who become pregnant during this trial, no episodes of teratogenicity occurred; 2 patients had normal deliveries, 2 had first-trimester spontaneous abortions (1 patient had alcohol use disorder, and the other patient was living with HIV), 1 had an elective abortion, and 1 was lost to follow-up (24). In analysis evaluating safety and pregnancy outcomes among pregnant women who were inadvertently exposed to study medications in 2 Tuberculosis Trials Consortium Study latent tuberculosis treatment trials (PREVENT TB and iAdhere), evaluating 3 months of weekly rifapentine (900 mg) with isoniazid and 9 months of daily isoniazid, fetal loss or congenital anomalies were at similar rates to the general population (26). Among 50 women enrolled in the IMPAACT 2001 trial, designed to assess 3 months of weekly rifapentine with isoniazid for TB prevention in pregnant women during the second or third trimester, with or without HIV, no drug-related serious AEs, treatment discontinuations, or TB cases were reported, although 1 case of fetal death was related to maternal physical trauma (27). The DOLPHIN-Moms trial, assessing 1 month of daily isoniazid and rifapentine versus 3 months of once-weekly rifapentine and isoniazid in pregnancy, is currently enrolling (28).
Concerning fluoroquinolone use in pregnancy, animal studies showed delayed skeletal development in fetal rats and rabbits when exposed to moxifloxacin and toxic cartilage effects in immature dogs when exposed to temafloxacin (9,29). However, in human studies, a metaanalysis that included 5 studies on use of quinolones during the first trimester of pregnancy did not find an increased risk for major malformations, stillbirths, preterm births, or low birthweight (30). A small case series of pregnant women with drug-resistant TB treated with second-line drugs, including fluoroquinolones, suggested that favorable pregnancy outcomes are achievable (31–34). A systematic review and metaanalysis of outcomes of pregnancies exposed to quinolone and fluoroquinolones, involving 8 cohort and 2 case–control studies, showed no statistically significant increases in rates of major malformations for quinolone and fluoroquinolone exposures (35).
Our study expands the scientific literature with additional data on rifapentine, moxifloxacin, pyrazinamide, and isoniazid early in pregnancy. We found that relatively brief exposures to rifapentine and moxifloxacin early in pregnancy were not associated with adverse fetal or maternal outcomes. However, the effect of longer exposures to rifapentine and moxifloxacin and effect of exposures later in pregnancy on maternal and fetal outcomes remains unknown, given that the trial specified immediate study treatment discontinuation and transition to local standard of care when a pregnancy was recognized. Our findings can help support and accelerate the participation of pregnant women in TB drug trials. In addition, publication of the detailed methodology used in this study to estimate the date of conception and total period of drug exposure during pregnancy might inform other clinical trials and thus help develop much needed harmonized reporting of safety outcomes among pregnant trial participants.
One limitation of our study is that the number of participants who became pregnant during study treatment was small, probably because of rigorous education of study participants of childbearing potential about contraception and preventing pregnancy during study treatment. The small number of pregnant participants limited the ability to detect rare events that can only be detected in larger trials and through pharmacovigilance efforts in the future. In addition, in participants who became pregnant, durations of exposures to study drugs were short, given that the protocol required immediate study treatment discontinuation in pregnancy. Adverse pregnancy events that require a higher cumulative exposure to study drugs to occur might not have been observed, so results should be interpreted in light of the short exposures. However, an average of 30 days of drug exposure during first trimester is a relatively long period of drug exposure and should not be dismissed. Furthermore, because fetal organogenesis primarily occurs in the first trimester, it is reassuring that only 1 infant with a congenital anomaly was observed among pregnancies exposed to rifapentine. In addition, because the study protocol required permanent discontinuation of the study treatment if a participant became pregnant (and transition to local standard of care), most participants who became pregnant during study treatment had their primary study TB treatment efficacy outcome classified as not assessable. Although final pregnancy outcomes were collected in the database for all participants, final TB treatment outcomes (after permanent stop of study treatment and switching to the local standard of care regimen) were not. Moreover, the study did not assess congenital anomalies among fetal deaths or spontaneous abortions. Finally, because study arms contained multiple study drugs, we cannot determine the effect of any single drug on adverse pregnancy outcomes. However, anti-TB drugs are commonly used in pregnancy, given the urgency of providing swift, full treatment for TB as soon as it is diagnosed.
In conclusion, among exposed pregnancies in this large phase 3 drug-susceptible pulmonary TB treatment trial, we did not observe a higher risk for fetal loss or infants with congenital anomalies among those participants who became pregnant while receiving a rifapentine/moxifloxacin regimen compared with the standard 6-month regimen. Those data can be used by clinicians and patients as they engage in shared decision-making and weigh the risks and benefits of using a shorter-duration 4-month rifapentine/moxifloxacin regimen versus a 6-month standard-of-care regimen in pregnancy, especially in the circumstance where an on-treatment pregnancy occurs. Future trials of rifapentine/moxifloxacin-containing regimens should consider allowing reconsent for participants who become pregnant during study treatment so that they can continue these study drugs with careful follow-up if there is potential benefit and there are no contraindications (36). The data from our study contribute to the growing body of information about the safety of rifapentine-containing regimens in pregnancy, which should support fuller participation of pregnant women in future TB clinical trials that include these antibiotics.
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Members of the AIDS Clinical Trials Group A5349: TASK, South Africa; University of Cape Town Lung Institute, South Africa; Les Centre GHESKIO INLR, Haiti; Parirenyatwa Clinical Research Site, Zimbabwe; South African Tuberculosis Vaccine Initiative, South Africa; Wits Helen Joseph Clinical Research Site Department of Medicine, South Africa; Les Centre GHESKIO IMIS, Haiti; Soweto ACTG Clinical Research Site, South Africa; Byramjee Jeejeebhoy Medical College, India; University of North Carolina Project Tidziwe Centre, Malawi; Kisumu Clinical Research Site, Kenya; Instituto Nacional de Pesquisa Clinica Evandro Chagas, Brazil; Blantyre Clinical Research Site/Johns Hopkins Research Project, Malawi; Family Clinical Research Unit (FAMCRU), South Africa; Durban International Clinical Research Site, South Africa; Moi University Clinical Research Site, Kenya; San Miguel Clinical Research Site, Peru; Asociacion Civil Impacta Salud y Educacion, Peru; Joint Clinical Research Center, Kampala Clinical Research Site, Uganda; Kenya Medical Research Institute/Walter Reed Project Clinical Research Center, Kenya; The Thai Red Cross AIDS Research Centre, Thailand; Chiang Mai University HIV Treatment Clinical Research Site, Thailand; Hospital Conceicao Porto Alegre, Brazil; and University of California San Francisco Clinical Research Site, USA.
Members of the Tuberculosis Trials Consortium Study 31: Uganda-Case Western Reserve University Research Collaboration, Uganda; Vietnam National Tuberculosis Program/University of California San Francisco Research Collaboration, Vietnam; Wits Health Consortium Perinatal HIV Research Unit (PHRU), South Africa; Tuberculosis and Chest Service of Hong Kong, China; San Antonio Veterans Administration Medical Center, USA; Universidad Peruana Cayetano Heredia, Peru; University of North Texas Health Science Center, USA; Columbia University, USA; Austin Tuberculosis Clinic, USA; and Baylor College of Medicine and Affiliated Hospitals/VA, USA.
We are grateful to the study participants who contributed their time to this trial and site and local tuberculosis program staff who assisted in the clinical management of study participants.
We are saddened to share that our colleague and coauthor William C. Whitworth passed away prior to the publication of this article. His insight and dedication greatly shaped this work.
Funding support for this trial was provided by the Centers for Disease Control and Prevention, National Center for HIV, Viral Hepatitis, STD, and Tuberculosis Prevention, Division of Tuberculosis Elimination (contract nos. 200-2009-32582, 200-2009-32593, 200-2009-32594, 200-2009-32589, 200-2009-32597, 200-2009-32598, 75D30119C06702, 75D30119C06701, 75D30119C06703, 75D30119C06222, 75D30119C06225, and 75D30119C06010) and by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health (award nos. UM1 AI068634, UM1 AI068636, and UM1 AI106701). Sanofi donated rifapentine and all other study drugs, supported shipping of study drugs to all sites, and provided funding support for pharmacokinetic testing and preparation of the final clinical study in this collaborative study.
Author contributions: study conception and design (E.V.K., W.C.W., P.J.P.P., N.A.S., S.S., R.E.C., S.E.D., and P.N.); data collection (E.V.K., W.C.W., K.E.B., N.A.S., N.E.B., K.H., L.P.P., G.M., R.D., Z.W., W.C., S.S., R.E.C., S.E.D., and P.N.); data analysis (W.C.W., P.J.P.P., N.A.S., and K.E.B.); data interpretation (E.V.K., W.C.W., L.P.P., P.J.P.P., N.A.S., K.E.B., P.J.P.P., W.C., K.E.D., S.S., R.E.C., S.E.D., and P.N.); drafting of the initial manuscript (E.V.K., W.C.W., M.D., K.E.D., and P.J.P.P.); critical review of the final draft of the manuscript (E.V.K., W.C.W., K.E.B., N.A.S., M.D., J.S.V.M., P.J.P.P., R.B., N.E.B., K.H., W.C., L.P.P., G.M., R.D., Z.W., K.E.D., S.S., R.E.C., S.E.D., and P.N.); and access and verification of underlying data (W.C.W., P.J.P.P., N.A.S., and K.E.B.).
The authorship team members have declared any potential conflicts of interest with respect to the research, authorship, or publication of this article. Sanofi commercial interests did not influence the study design; the collection, analysis, or interpretation of data; the preparation of this manuscript; or the decision to submit this manuscript for publication. A Sanofi technical expert served on the protocol team.
It wasn’t until a couple of years ago that Keri Rodrigues began to worry about how her kids might be using chatbots. She learned her youngest son was interacting with the chatbot in his Bible app — he was asking it some deep moral questions, about sin for instance.
That’s the kind of conversation that she had hoped her son would have with her and not a computer. “Not everything in life is black and white,” she says. “There are grays. And it’s my job as his mom to help him navigate that and walk through it, right?”
Rodrigues has also been hearing from parents across the country who are concerned about AI chatbots’ influence on their children. She is the president of the National Parents Union, which advocates for children and families. Many parents, she says, are watching chatbots claim to be their kids’ best friends, encouraging children to tell them everything.
Psychologists and online safety advocates say parents are right to be worried. Extended chatbot interactions may affect kids’ social development and mental health, they say. And the technology is changing so fast that few safeguards are in place.
The impacts can be serious. According to their parents’ testimonies at a recent Senate hearing, two teens died by suicide after prolonged interactions with chatbots that encouraged their suicide plans.
If you or someone you know may be considering suicide or be in crisis, call or text988 to reach the 988 Suicide & Crisis Lifeline.
But generative AI chatbots are a growing part of life for American teens. A survey by the Pew Research Center found that 64% of adolescents are using chatbots, with 3 in 10 saying they use them daily.
“It’s a very new technology,” says Dr. Jason Nagata, a pediatrician and researcher of adolescent digital media use at the University of California San Francisco. “It’s ever-changing and there’s not really best practices for youth yet. So, I think there are more opportunities now for risks because we’re still kind of guinea pigs in the whole process.”
And teenagers are particularly vulnerable to the risks of chatbots, he adds, because adolescence is a time of rapid brain development, which is shaped by experiences. “It is a period when teens are more vulnerable to lots of different exposures, whether it’s peers or computers.”
But parents can minimize those risks, say pediatricians and psychologists. Here are some ways to help teens navigate the technology safely.
1. Be aware of the risks
A new report from the online safety company, Aura, shows that 42% of adolescents using AI chatbots use them for companionship. Aura gathered data from the daily device use of 3,000 teens as well as surveys of families.
That includes some disturbing conversations involving violence and sex, says psychologist Scott Kollins, chief medical officer at Aura, who leads the company’s research on teen interactions with generative AI.
“It is role play that is [an] interaction about harming somebody else, physically hurting them, torturing them,” he says.
He says it’s normal for kids to be curious about sex, but learning about sexual interactions from a chatbot instead of a trusted adult is problematic.
And chatbots are designed to agree with users, says pediatrician Nagata. So if your child starts a query about sex or violence, “the default of the AI is to engage with it and to reinforce it.”
He says spending a lot of time with chatbots — having extended conversations — also prevents teenagers from learning important social skills, like empathy, reading body language and negotiating differences.
“When you’re only or exclusively interacting with computers who are agreeing with you, then you don’t get to develop those skills,” he says.
And there are mental health risks. According to a recent study by researchers at the nonprofit research organization RAND, Harvard and Brown universities, 1 in 8 adolescents and young adults use chatbots for mental health advice.
But there have been numerous reports of individuals experiencing delusions, or what’s being referred to as AI psychosis, after prolonged interactions with chatbots. This, as well as the concern over risks of suicide, has led psychologists to warn that AI chatbots pose serious risks to the mental health and safety of teens as well as vulnerable adults.
“We see that when people interact with [chatbots] over long periods of time, that things start to degrade, that the chatbots do things that they’re not intended to do,” says psychologist Ursula Whiteside, CEO of a mental health nonprofit called Now Matters Now. For example, she says, chatbots “give advice about lethal means, things that it’s not supposed to do but does happen over time with repeated queries.”
2. Stay engaged with kids’ online lives
Keep an open dialogue going with your child, says Nagata.
“Parents don’t need to be AI experts,” he says. “They just need to be curious about their children’s lives and ask them about what kind of technology they’re using and why.”
And have those conversations early and often, says psychologist Kollins of Aura.
“We need to have frequent and candid but nonjudgmental conversations with our kids about what this content looks like,” says Kollins, who’s also a father to two teenagers. “And we’re going to have to continue to do that.”
He often asks his teens about what platforms they are on. When he hears about new chatbots through his own research at Aura, he also asks his kids if they have heard of those or used them.
“Don’t blame the child for expressing or taking advantage of something that’s out there to satisfy their natural curiosity and exploration,” he says.
And make sure to keep the conversations open-ended, says Nagata: “I do think that that allows for your teenager or child to open up about problems that they’ve encountered.”
3. Develop digital literacy
It’s also important to talk to kids about the benefits and pitfalls of generative AI. And if parents don’t understand all the risks and benefits, parents and kids can research that together, suggests psychologist Jacqueline Nesi at Brown University, who was involved in the American Psychological Association’s recent health advisory on AI and adolescent health.
“A certain amount of digital literacy and literacy does need to happen at home,” she says.
It’s important for parents and teens to understand that while chatbots can help with research, they also make errors, says Nagata. And it is important for users to be skeptical and fact-check.
“Part of this education process for children is to help them to understand that this is not the final say,” explains Nagata. “You yourself can process this information and try to assess, what’s real or not. And if you’re not sure, then try to verify with other people or other sources.”
4. Parental controls only work if kids set up their own accounts
If a child is using AI chatbots, it may be better for them to set up their own account on the platforms, says Nesi, instead of using chatbots anonymously.
“Many of the more popular platforms now have parental controls in place,” she says. “But in order for those parental controls to be in effect, a child does need to have their own account.”
But be aware, there are dozens of different AI chatbots that kids could be using. “We identified 88 different AI platforms that kids were interacting with,” says Kollins.
This underscores the importance of having an open dialogue with your child to stay aware of what they’re using.
5. Set time limits
Nagata also advises setting boundaries around when kids use digital technology, especially at nighttime.
“One potential aspect of generative AI that can also lead to mental health and physical health impacts are [when] kids are chatting all night long and it’s really disrupting their sleep,” says Nagata. “Because they’re very personalized conversations, they’re very engaging. Kids are more likely to continue to engage and have more and more use.”
And if a child is veering toward overuse and misuse of generative AI, Nagata recommends that parents set time limits or limit certain kinds of content on chatbots.
6. Seek help for more vulnerable teens
Kids who are already struggling with their mental health or social skills are more likely to be vulnerable to the risks of chatbots, says Nesi.
“So if they’re already lonely, if they’re already isolated, then I think there’s a bigger risk that maybe a chatbot could then exacerbate those issues,” she says.
And it’s also important to keep an eye on potential warning signs of poor mental health, she notes.
Those warning signs involve sudden and persistent changes in mood, isolation or changes in how engaged they are at school.
“Parents should be as much as possible trying to pay attention to the whole picture of the child,” says Nesi. “How are they doing in school? How are they doing with friends? How are they doing at home if they are starting to withdraw?”
If a teen is withdrawing from friends and family and restricting their social interactions to just the chatbot, that too is a warning sign, she says. “Are they going to the chatbot instead of a friend or instead of a therapist or instead of responsible adults about serious issues?
Also look for signs of dependence or addiction to a chatbot, she adds. “Are they having difficulty controlling how much they are using a chatbot? Like, is it starting to feel like it’s controlling them? They kind of can’t stop,” she says.
And if they see those signs, parents should reach out to a professional for help, says Nesi.
“Speaking to a child’s pediatrician is always a good first step,” she says. “But in most cases, getting a mental health professional involved is probably going to make sense.”
7. The government has a role to play
But, she acknowledges that the job of keeping children and teens safe from this technology shouldn’t just fall upon parents.
“There’s a responsibility, you know, from lawmakers, from the companies themselves to make these products safe for teens.”
Lawmakers in Congress recently introduced bipartisan legislation to ban tech companies from offering companion apps for minors and to hold companies accountable for making available to minors companion apps that produce or solicit sexual content.
If you or someone you know may be considering suicide or be in crisis, call or text988 to reach the 988 Suicide & Crisis Lifeline.
The U.S. Food and Drug Administration today released a congressionally mandated report under the Modernization of Cosmetics Regulation Act of 2022 (MoCRA) evaluating the use of perfluoroalkyl and polyfluoroalkyl substances (PFAS) in cosmetic products. While the report reviews available scientific evidence on potential safety concerns, the FDA’s evaluation did not reach definitive safety determinations and underscores significant uncertainty due to gaps in existing data on PFAS exposure through cosmetics.
“In accordance with our congressional mandate, the FDA today released its assessment of PFAS in cosmetic products,” said FDA Commissioner Marty Makary, M.D., M.P.H. “Our scientists found that toxicological data for most PFAS are incomplete or unavailable, leaving significant uncertainty about consumer safety. This lack of reliable data demands further research. Consistent with the MAHA Strategy Report, the FDA will continue working with the CDC and EPA to update and strengthen recommendations on PFAS across the retail and food supply chain.”
Based on mandatory cosmetic product listing data submitted to the FDA, 51 PFAS are used in 1,744 cosmetic formulations. To assess safety, the FDA evaluated the 25 most frequently used PFAS, which represent approximately 96% of PFAS intentionally added to cosmetic products. The agency found that “toxicological data for a majority of these PFAS are incomplete or unavailable,” limiting its ability to fully assess risk. The FDA’s ability to effectively collect toxicology data was limited by the fact that most of the data is not publicly available. While five PFAS appeared to present low safety concerns under their intended conditions of use, the safety of most PFAS could not be definitively established, and one PFAS was identified as having a potential safety concern with significant remaining uncertainty.
The report focuses on PFAS intentionally added to cosmetic products as ingredients, rather than PFAS that may be present as contaminants. PFAS are synthetic chemicals used for properties such as water resistance, durability, and texture modification, but their persistence and potential toxicity have raised health and environmental concerns and prompted increasing regulatory scrutiny at the state, federal, and global levels.
There are currently no federal regulations that specifically prohibit PFAS intentionally added to cosmetic products. However, consistent with FDA enforcement policies, the agency will take appropriate action if safety concerns emerge related to such cosmetic products.
The FDA will continue to monitor emerging scientific data and devote additional resources to address data gaps, supporting the Department of Health and Human Services’ Make America Healthy Again efforts to reduce PFAS across the food and consumer product supply chain through expanded testing, monitoring, and surveillance.
For more information on PFAS in cosmetic products, visit the FDA’s website: https://www.fda.gov/cosmetics/cosmetic-ingredients/and-polyfluoroalkyl-substances-pfas-cosmetics.
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