Using Artificial Intelligence and Machine Learning in the Development of Drug and Biological Products; Availability, 30313-30314 [2023-09985]

Download as PDF ddrumheller on DSK120RN23PROD with NOTICES1 Federal Register / Vol. 88, No. 91 / Thursday, May 11, 2023 / Notices suspends approval of the drug’s NDA or ANDA for reasons of safety or effectiveness or if FDA determines that the listed drug was withdrawn from sale for reasons of safety or effectiveness (21 CFR 314.162). A person may petition the Agency to determine, or the Agency may determine on its own initiative, whether a listed drug was withdrawn from sale for reasons of safety or effectiveness. This determination may be made at any time after the drug has been withdrawn from sale, but must be made prior to approving an ANDA that refers to the listed drug (§ 314.161 (21 CFR 314.161)). FDA may not approve an ANDA that does not refer to a listed drug. Hydrochlorothiazide oral solution, 50 mg/5 mL, is the subject of ANDA 088587, held by Roxane Laboratories Inc., and initially approved on July 2, 1984. Hydrochlorothiazide is indicated for: (1) adjunctive therapy in edema associated with congestive heart failure, hepatic cirrhosis, and corticosteroid and estrogen therapy; (2) edema due to various forms of renal dysfunction such as nephrotic syndrome, acute glomerulonephritis, and chronic renal failure; and (3) the management of hypertension either as the sole therapeutic agent or to enhance the effectiveness of other antihypertensive drugs in the more severe form of hypertension. In a letter dated August 4, 2008, Roxane Laboratories Inc. requested withdrawal of ANDA 088587 for hydrochlorothiazide oral solution. In the Federal Register issue of July 21, 2010 (75 FR 42455), FDA announced that it was withdrawing approval of ANDA 088587, effective August 20, 2010. Hyman, Phelps & McNamara, P.C. submitted a citizen petition dated September 13, 2022 (Docket No. FDA– 2022–P–2229), under 21 CFR 10.30, requesting that the Agency determine whether hydrochlorothiazide oral solution, 50 mg/5 mL, was withdrawn from sale for reasons of safety or effectiveness. After considering the citizen petition and reviewing Agency records and based on the information we have at this time, FDA has determined under § 314.161 that hydrochlorothiazide oral solution, 50 mg/5 mL, was not withdrawn for reasons of safety or effectiveness. The petitioner has identified no data or other information suggesting that this product was withdrawn for reasons of safety or effectiveness. We have carefully reviewed our files for records concerning the withdrawal of hydrochlorothiazide oral solution, 50 VerDate Sep<11>2014 17:07 May 10, 2023 Jkt 259001 mg/5 mL, from sale. We have also independently evaluated relevant literature and data for possible postmarketing adverse events. We have reviewed the available evidence and determined that this drug product was not withdrawn from sale for reasons of safety or effectiveness. Accordingly, the Agency will continue to list hydrochlorothiazide oral solution, 50 mg/5 mL, in the ‘‘Discontinued Drug Product List’’ section of the Orange Book. The ‘‘Discontinued Drug Product List’’ delineates, among other items, drug products that have been discontinued from marketing for reasons other than safety or effectiveness. ANDAs that refer to this drug product may be approved by the Agency as long as they meet all other legal and regulatory requirements for the approval of ANDAs. If FDA determines that labeling for this drug product should be revised to meet current standards, the Agency will advise ANDA applicants to submit such labeling. Dated: May 8, 2023. Lauren K. Roth, Associate Commissioner for Policy. [FR Doc. 2023–10052 Filed 5–10–23; 8:45 am] BILLING CODE 4164–01–P DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration [Docket No. FDA–2023–N–0743] Using Artificial Intelligence and Machine Learning in the Development of Drug and Biological Products; Availability AGENCY: Food and Drug Administration, HHS. ACTION: Notice of availability. The Food and Drug Administration (FDA or Agency) is announcing the publication of a discussion paper entitled ‘‘Using Artificial Intelligence and Machine Learning in the Development of Drug and Biological Products.’’ To fulfill its mission of protecting, promoting, and advancing public health, FDA’s Center for Drug Evaluation and Research (CDER), in collaboration with the Center for Biologics Evaluation and Research (CBER) and Center for Devices and Radiological Health (CDRH), including the Digital Health Center of Excellence (DHCoE), is issuing this document to facilitate a discussion with stakeholders on the use of artificial intelligence (AI) and machine learning (ML) in drug SUMMARY: PO 00000 Frm 00038 Fmt 4703 Sfmt 4703 30313 development to help inform the regulatory landscape in this area. DATES: Either electronic or written comments on the framework must be submitted by August 9, 2023. ADDRESSES: You may submit comments as follows. Please note that late, untimely filed comments will not be considered. The https:// www.regulations.gov electronic filing system will accept comments until 11:59 p.m. Eastern Time at the end of August 9, 2023. Comments received by mail/hand delivery/courier (for written/ paper submissions) will be considered timely if they are received on or before that date. Electronic Submissions Submit electronic comments in the following way: • Federal eRulemaking Portal: https://www.regulations.gov. Follow the instructions for submitting comments. Comments submitted electronically, including attachments, to https:// www.regulations.gov will be posted to the docket unchanged. Because your comment will be made public, you are solely responsible for ensuring that your comment does not include any confidential information that you or a third party may not wish to be posted, such as medical information, your or anyone else’s Social Security number, or confidential business information, such as a manufacturing process. Please note that if you include your name, contact information, or other information that identifies you in the body of your comments, that information will be posted on https://www.regulations.gov. • If you want to submit a comment with confidential information that you do not wish to be made available to the public, submit the comment as a written/paper submission and in the manner detailed (see ‘‘Written/Paper Submissions’’ and ‘‘Instructions’’). Written/Paper Submissions Submit written/paper submissions as follows: • Mail/Hand Delivery/Courier (for written/paper submissions): Dockets Management Staff (HFA–305), Food and Drug Administration, 5630 Fishers Lane, Rm. 1061, Rockville, MD 20852. • For written/paper comments submitted to the Dockets Management Staff, FDA will post your comment, as well as any attachments, except for information submitted, marked and identified, as confidential, if submitted as detailed in ‘‘Instructions.’’ Instructions: All submissions received must include the Docket No. FDA– 2023–N–0743 for ‘‘Using Artificial E:\FR\FM\11MYN1.SGM 11MYN1 ddrumheller on DSK120RN23PROD with NOTICES1 30314 Federal Register / Vol. 88, No. 91 / Thursday, May 11, 2023 / Notices Intelligence and Machine Learning in the Development of Drug and Biological Products.’’ Received comments, those filed in a timely manner (see ADDRESSES), will be placed in the docket and, except for those submitted as ‘‘Confidential Submissions,’’ publicly viewable at https://www.regulations.gov or at the Dockets Management Staff between 9 a.m. and 4 p.m., Monday through Friday, 240–402–7500. • Confidential Submissions—To submit a comment with confidential information that you do not wish to be made publicly available, submit your comments only as a written/paper submission. You should submit two copies total. One copy will include the information you claim to be confidential with a heading or cover note that states ‘‘THIS DOCUMENT CONTAINS CONFIDENTIAL INFORMATION.’’ The Agency will review this copy, including the claimed confidential information, in its consideration of comments. The second copy, which will have the claimed confidential information redacted/blacked out, will be available for public viewing and posted on https://www.regulations.gov. Submit both copies to the Dockets Management Staff. If you do not wish your name and contact information to be made publicly available, you can provide this information on the cover sheet and not in the body of your comments and you must identify this information as ‘‘confidential.’’ Any information marked as ‘‘confidential’’ will not be disclosed except in accordance with 21 CFR 10.20 and other applicable disclosure law. For more information about FDA’s posting of comments to public dockets, see 80 FR 56469, September 18, 2015, or access the information at: https:// www.govinfo.gov/content/pkg/FR-201509-18/pdf/2015-23389.pdf. Docket: For access to the docket to read background documents or the electronic and written/paper comments received, go to https:// www.regulations.gov and insert the docket number, found in brackets in the heading of this document, into the ‘‘Search’’ box and follow the prompts and/or go to the Dockets Management Staff, 5630 Fishers Lane, Rm. 1061, Rockville, MD 20852, 240–402–7500. FOR FURTHER INFORMATION CONTACT: Tala Fakhouri, Center for Drug Evaluation and Research, Food and Drug Administration, 10903 New Hampshire Ave., Bldg. 51, Rm. 6330, Silver Spring, MD 20993–0002, 301–837–7407, Tala.Fakhouri@fda.hhs.gov; Janice Maniwang, Center for Drug Evaluation and Research, Food and Drug Administration, 10903 New Hampshire VerDate Sep<11>2014 17:07 May 10, 2023 Jkt 259001 Ave., Bldg. 51, Rm. 6316, Silver Spring, MD 20993–0002, 301–796–3821, Janice.Maniwang@fda.hhs.gov; or Hussein Ezzeldin, Center for Biologics Evaluation and Research, Food and Drug Administration, 10903 New Hampshire Ave., Bldg. 71, Rm. 5246, Silver Spring, MD 20993–0002, 240– 402–8629, Hussein.Ezzeldin@ fda.hhs.gov; or Brendan O’Leary, Center for Devices and Radiological Health, Food and Drug Administration, 10903 New Hampshire Ave., Bldg. 66, Rm. 5530, Silver Spring, MD 20993–0002, 301–796–6898, Brendan.OLeary@ fda.hhs.gov. SUPPLEMENTARY INFORMATION: I. Background FDA aims to ensure safety and effectiveness while facilitating innovations in the development of drugs. Recent rapid technological innovations in sophisticated data collection and generation tools, combined with robust information management and exchange systems, and advanced computing abilities may prove transformational in the way drugs are developed and used.1 This evolving ecosystem presents unique opportunities and challenges, and FDA is committed to working across its medical product centers with partners domestically and internationally to ensure that the full potential of these innovations is realized for the benefit of the public. Developers, manufacturers, regulators, academic groups, and other stakeholders are working to develop a shared understanding of where and how specific innovations, such as AI and ML, can best be utilized across the drug development process, including through the use of AI/ML-enabled tools, which may include devices. FDA is publishing this discussion paper as part of a multifaceted approach to enhance mutual learning and to establish a dialogue with FDA stakeholders on this topic. While AI and ML are not consistently defined across all disciplines and stakeholders, AI can be generally described as a branch of computer science, statistics, and engineering that uses algorithms or models to perform tasks and exhibit behaviors such as learning, making decisions, and making predictions. ML is generally considered a subset of AI that allows ML models to be developed by ML training algorithms through analysis of data, without models being explicitly programmed. Additionally, there are a variety of ML methods and 1 See different types of algorithms that may be utilized in a given context. For the purposes of this discussion paper, AI and ML will be referenced together as AI/ML, and references to drug development and the drug development process include a wide scope of activities and phases, including manufacturing and surveillance, among others. This discussion paper, which considers the application of AI/ML in the broad context of the drug development process, is not FDA guidance or policy, and is not meant to endorse a specific AI/ML use or approach in drug development. Rather, it is an initial communication with stakeholders, including academic groups, that is intended to promote mutual learning and discussion. Specifically, FDA is soliciting feedback on the opportunities and challenges with utilizing AI/ML in the development of drugs, as well as in the development of medical devices intended to be used with drugs. This feedback will provide an additional resource to help inform the regulatory landscape in this area. Additionally, it is beneficial for researchers and technology developers, particularly those new to drug development and human subjects research, to recognize some of the initial thinking and considerations involved with utilizing these technologies, including having familiarity with FDA’s current activities, initiatives, practices, and potentially applicable regulations. II. Electronic Access Persons with access to the internet may obtain the discussion paper, ‘‘Using Artificial Intelligence and Machine Learning in the Development of Drug and Biological Products: Discussion Paper’’ at https://www.fda.gov/scienceresearch/science-and-research-specialtopics/artificial-intelligence-andmachine-learning-aiml-drugdevelopment. Dated: May 5, 2023. Lauren K. Roth, Associate Commissioner for Policy. [FR Doc. 2023–09985 Filed 5–10–23; 8:45 am] BILLING CODE 4164–01–P https://pubmed.ncbi.nlm.nih.gov/35319833/ . PO 00000 Frm 00039 Fmt 4703 Sfmt 9990 E:\FR\FM\11MYN1.SGM 11MYN1

Agencies

[Federal Register Volume 88, Number 91 (Thursday, May 11, 2023)]
[Notices]
[Pages 30313-30314]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2023-09985]


-----------------------------------------------------------------------

DEPARTMENT OF HEALTH AND HUMAN SERVICES

Food and Drug Administration

[Docket No. FDA-2023-N-0743]


Using Artificial Intelligence and Machine Learning in the 
Development of Drug and Biological Products; Availability

AGENCY: Food and Drug Administration, HHS.

ACTION: Notice of availability.

-----------------------------------------------------------------------

SUMMARY: The Food and Drug Administration (FDA or Agency) is announcing 
the publication of a discussion paper entitled ``Using Artificial 
Intelligence and Machine Learning in the Development of Drug and 
Biological Products.'' To fulfill its mission of protecting, promoting, 
and advancing public health, FDA's Center for Drug Evaluation and 
Research (CDER), in collaboration with the Center for Biologics 
Evaluation and Research (CBER) and Center for Devices and Radiological 
Health (CDRH), including the Digital Health Center of Excellence 
(DHCoE), is issuing this document to facilitate a discussion with 
stakeholders on the use of artificial intelligence (AI) and machine 
learning (ML) in drug development to help inform the regulatory 
landscape in this area.

DATES: Either electronic or written comments on the framework must be 
submitted by August 9, 2023.

ADDRESSES: You may submit comments as follows. Please note that late, 
untimely filed comments will not be considered. The https://www.regulations.gov electronic filing system will accept comments until 
11:59 p.m. Eastern Time at the end of August 9, 2023. Comments received 
by mail/hand delivery/courier (for written/paper submissions) will be 
considered timely if they are received on or before that date.

Electronic Submissions

    Submit electronic comments in the following way:
     Federal eRulemaking Portal: https://www.regulations.gov. 
Follow the instructions for submitting comments. Comments submitted 
electronically, including attachments, to https://www.regulations.gov 
will be posted to the docket unchanged. Because your comment will be 
made public, you are solely responsible for ensuring that your comment 
does not include any confidential information that you or a third party 
may not wish to be posted, such as medical information, your or anyone 
else's Social Security number, or confidential business information, 
such as a manufacturing process. Please note that if you include your 
name, contact information, or other information that identifies you in 
the body of your comments, that information will be posted on https://www.regulations.gov.
     If you want to submit a comment with confidential 
information that you do not wish to be made available to the public, 
submit the comment as a written/paper submission and in the manner 
detailed (see ``Written/Paper Submissions'' and ``Instructions'').

Written/Paper Submissions

    Submit written/paper submissions as follows:
     Mail/Hand Delivery/Courier (for written/paper 
submissions): Dockets Management Staff (HFA-305), Food and Drug 
Administration, 5630 Fishers Lane, Rm. 1061, Rockville, MD 20852.
     For written/paper comments submitted to the Dockets 
Management Staff, FDA will post your comment, as well as any 
attachments, except for information submitted, marked and identified, 
as confidential, if submitted as detailed in ``Instructions.''
    Instructions: All submissions received must include the Docket No. 
FDA-2023-N-0743 for ``Using Artificial

[[Page 30314]]

Intelligence and Machine Learning in the Development of Drug and 
Biological Products.'' Received comments, those filed in a timely 
manner (see ADDRESSES), will be placed in the docket and, except for 
those submitted as ``Confidential Submissions,'' publicly viewable at 
https://www.regulations.gov or at the Dockets Management Staff between 
9 a.m. and 4 p.m., Monday through Friday, 240-402-7500.
     Confidential Submissions--To submit a comment with 
confidential information that you do not wish to be made publicly 
available, submit your comments only as a written/paper submission. You 
should submit two copies total. One copy will include the information 
you claim to be confidential with a heading or cover note that states 
``THIS DOCUMENT CONTAINS CONFIDENTIAL INFORMATION.'' The Agency will 
review this copy, including the claimed confidential information, in 
its consideration of comments. The second copy, which will have the 
claimed confidential information redacted/blacked out, will be 
available for public viewing and posted on https://www.regulations.gov. 
Submit both copies to the Dockets Management Staff. If you do not wish 
your name and contact information to be made publicly available, you 
can provide this information on the cover sheet and not in the body of 
your comments and you must identify this information as 
``confidential.'' Any information marked as ``confidential'' will not 
be disclosed except in accordance with 21 CFR 10.20 and other 
applicable disclosure law. For more information about FDA's posting of 
comments to public dockets, see 80 FR 56469, September 18, 2015, or 
access the information at: https://www.govinfo.gov/content/pkg/FR-2015-09-18/pdf/2015-23389.pdf.
    Docket: For access to the docket to read background documents or 
the electronic and written/paper comments received, go to https://www.regulations.gov and insert the docket number, found in brackets in 
the heading of this document, into the ``Search'' box and follow the 
prompts and/or go to the Dockets Management Staff, 5630 Fishers Lane, 
Rm. 1061, Rockville, MD 20852, 240-402-7500.

FOR FURTHER INFORMATION CONTACT: Tala Fakhouri, Center for Drug 
Evaluation and Research, Food and Drug Administration, 10903 New 
Hampshire Ave., Bldg. 51, Rm. 6330, Silver Spring, MD 20993-0002, 301-
837-7407, [email protected]; Janice Maniwang, Center for Drug 
Evaluation and Research, Food and Drug Administration, 10903 New 
Hampshire Ave., Bldg. 51, Rm. 6316, Silver Spring, MD 20993-0002, 301-
796-3821, [email protected]; or Hussein Ezzeldin, Center for 
Biologics Evaluation and Research, Food and Drug Administration, 10903 
New Hampshire Ave., Bldg. 71, Rm. 5246, Silver Spring, MD 20993-0002, 
240-402-8629, [email protected]; or Brendan O'Leary, Center 
for Devices and Radiological Health, Food and Drug Administration, 
10903 New Hampshire Ave., Bldg. 66, Rm. 5530, Silver Spring, MD 20993-
0002, 301-796-6898, [email protected].

SUPPLEMENTARY INFORMATION: 

I. Background

    FDA aims to ensure safety and effectiveness while facilitating 
innovations in the development of drugs. Recent rapid technological 
innovations in sophisticated data collection and generation tools, 
combined with robust information management and exchange systems, and 
advanced computing abilities may prove transformational in the way 
drugs are developed and used.\1\ This evolving ecosystem presents 
unique opportunities and challenges, and FDA is committed to working 
across its medical product centers with partners domestically and 
internationally to ensure that the full potential of these innovations 
is realized for the benefit of the public.
---------------------------------------------------------------------------

    \1\ See https://pubmed.ncbi.nlm.nih.gov/35319833/.
---------------------------------------------------------------------------

    Developers, manufacturers, regulators, academic groups, and other 
stakeholders are working to develop a shared understanding of where and 
how specific innovations, such as AI and ML, can best be utilized 
across the drug development process, including through the use of AI/
ML-enabled tools, which may include devices. FDA is publishing this 
discussion paper as part of a multifaceted approach to enhance mutual 
learning and to establish a dialogue with FDA stakeholders on this 
topic. While AI and ML are not consistently defined across all 
disciplines and stakeholders, AI can be generally described as a branch 
of computer science, statistics, and engineering that uses algorithms 
or models to perform tasks and exhibit behaviors such as learning, 
making decisions, and making predictions. ML is generally considered a 
subset of AI that allows ML models to be developed by ML training 
algorithms through analysis of data, without models being explicitly 
programmed. Additionally, there are a variety of ML methods and 
different types of algorithms that may be utilized in a given context. 
For the purposes of this discussion paper, AI and ML will be referenced 
together as AI/ML, and references to drug development and the drug 
development process include a wide scope of activities and phases, 
including manufacturing and surveillance, among others.
    This discussion paper, which considers the application of AI/ML in 
the broad context of the drug development process, is not FDA guidance 
or policy, and is not meant to endorse a specific AI/ML use or approach 
in drug development. Rather, it is an initial communication with 
stakeholders, including academic groups, that is intended to promote 
mutual learning and discussion. Specifically, FDA is soliciting 
feedback on the opportunities and challenges with utilizing AI/ML in 
the development of drugs, as well as in the development of medical 
devices intended to be used with drugs. This feedback will provide an 
additional resource to help inform the regulatory landscape in this 
area. Additionally, it is beneficial for researchers and technology 
developers, particularly those new to drug development and human 
subjects research, to recognize some of the initial thinking and 
considerations involved with utilizing these technologies, including 
having familiarity with FDA's current activities, initiatives, 
practices, and potentially applicable regulations.

II. Electronic Access

    Persons with access to the internet may obtain the discussion 
paper, ``Using Artificial Intelligence and Machine Learning in the 
Development of Drug and Biological Products: Discussion Paper'' at 
https://www.fda.gov/science-research/science-and-research-special-topics/artificial-intelligence-and-machine-learning-aiml-drug-development.

    Dated: May 5, 2023.
Lauren K. Roth,
Associate Commissioner for Policy.
[FR Doc. 2023-09985 Filed 5-10-23; 8:45 am]
BILLING CODE 4164-01-P
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.