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1.
J Am Chem Soc ; 146(15): 10581-10590, 2024 Apr 17.
Article in English | MEDLINE | ID: mdl-38580459

ABSTRACT

Positron emission tomography is a widely used imaging platform for studying physiological processes. Despite the proliferation of modern synthetic methodologies for radiolabeling, the optimization of these reactions still primarily relies on inefficient one-factor-at-a-time approaches. High-throughput experimentation (HTE) has proven to be a powerful approach for optimizing reactions in many areas of chemical synthesis. However, to date, HTE has rarely been applied to radiochemistry. This is largely because of the short lifetime of common radioisotopes, which presents major challenges for efficient parallel reaction setup and analysis using standard equipment and workflows. Herein, we demonstrate an effective HTE workflow and apply it to the optimization of copper-mediated radiofluorination of pharmaceutically relevant boronate ester substrates. The workflow utilizes commercial equipment and allows for rapid analysis of reactions for optimizing reactions, exploring chemical space using pharmaceutically relevant aryl boronates for radiofluorinations, and constructing large radiochemistry data sets.


Subject(s)
Copper , Positron-Emission Tomography , Radiochemistry , Positron-Emission Tomography/methods , Radiopharmaceuticals , Fluorine Radioisotopes
2.
Org Lett ; 26(16): 3419-3423, 2024 Apr 26.
Article in English | MEDLINE | ID: mdl-38630573

ABSTRACT

We present a photo- and Cu-mediated 11C cyanation of bench-stable (hetero)aryl thianthrenium salts via an aryl radical addition pathway. The thianthrenium substrates can be readily accessed via C-H functionalization, and the radiocyanation protocol proceeds under mild conditions (<50 °C, 5 min) and can be automated using open-source, readily accessible augmentations to existing radiochemistry equipment.

3.
Angew Chem Int Ed Engl ; 63(2): e202316365, 2024 Jan 08.
Article in English | MEDLINE | ID: mdl-38010255

ABSTRACT

This report describes the development of a Zn(OTf)2 -mediated method for converting α-tertiary haloamides to the corresponding fluorine-18 labelled α-tertiary fluoroamides with no-carrier-added [18 F]tetramethylammonium fluoride. 1,5,7-Triazabicyclo[4.4.0]dec-5-ene is an essential additive for achieving high radiochemical conversion. Under the optimised conditions, radiofluorination proceeds at sterically hindered tertiary sites in high radiochemical conversions, yields, and purities. This method has been successfully automated and applied to access >200 mCi (>7.4 GBq) of several model radiofluorides. Mechanistic studies led to the development of a new, nucleophilic C-H radiofluorination process using N-sulphonyloxyamide substrates.

4.
J Am Chem Soc ; 145(12): 6921-6926, 2023 Mar 29.
Article in English | MEDLINE | ID: mdl-36917154

ABSTRACT

Radiocyanation is an attractive strategy for incorporating carbon-11 into radiotracer targets, particularly given the broad scope of acyl moieties accessible from nitriles. Most existing methods for aromatic radiocyanation require elevated temperatures (Cu-mediated reactions of aryl halides or organometallics) or involve expensive and toxic palladium complexes (Pd-mediated reactions of aryl halides). The current report discloses a complementary approach that leverages the capture of aryl radical intermediates by a Cu-11CN complex to achieve rapid and mild (5 min, room temperature) radiocyanation. In a first example, aryl radicals are generated via the reaction of a CuI mediator with an aryldiazonium salt (a Sandmeyer-type reaction) followed by radiocyanation with Cu-11CN. In a second example, aryl radicals are formed from aryl iodides via visible-light photocatalysis and then captured by a Cu-11CN species to achieve aryl-11CN coupling. This approach provides access to radiocyanated products that are challenging to access using other methods (e.g., ortho-disubstituted aryl nitriles).

5.
ACS Chem Neurosci ; 13(12): 1675-1683, 2022 06 15.
Article in English | MEDLINE | ID: mdl-35606334

ABSTRACT

Positron emission tomography (PET) is a highly sensitive and versatile molecular imaging modality that leverages radiolabeled molecules, known as radiotracers, to interrogate biochemical processes such as metabolism, enzymatic activity, and receptor expression. The ability to probe specific molecular and cellular events longitudinally in a noninvasive manner makes PET imaging a particularly powerful technique for studying the central nervous system (CNS) in both health and disease. Unfortunately, developing and translating a single CNS PET tracer for clinical use is typically an extremely resource-intensive endeavor, often requiring synthesis and evaluation of numerous candidate molecules. While existing in vitro methods are beginning to address the challenge of derisking molecules prior to costly in vivo PET studies, most require a significant investment of resources and possess substantial limitations. In the context of CNS drug development, significant time and resources have been invested into the development and optimization of computational methods, particularly involving machine learning, to streamline the design of better CNS therapeutics. However, analogous efforts developed and validated for CNS radiotracer design are conspicuously limited. In this Perspective, we overview the requirements and challenges of CNS PET tracer design, survey the most promising computational methods for in silico CNS drug design, and bridge these two areas by discussing the potential applications and impact of computational design tools in CNS radiotracer design.


Subject(s)
Positron-Emission Tomography , Radiopharmaceuticals , Central Nervous System , Central Nervous System Agents/pharmacology , Positron-Emission Tomography/methods , Radiopharmaceuticals/chemistry
6.
PET Clin ; 16(4): 525-532, 2021 Oct.
Article in English | MEDLINE | ID: mdl-34537128

ABSTRACT

Artificial intelligence and machine learning are poised to disrupt PET imaging from bench to clinic. In this perspective, the authors offer insights into how the technology could be applied to improve the radiosynthesis of new radiopharmaceuticals for PET imaging, including identification of an optimal labeling approach as well as strategies for radiolabeling reaction optimization.


Subject(s)
Artificial Intelligence , Radiopharmaceuticals , Fluorine Radioisotopes , Humans , Machine Learning , Positron-Emission Tomography , Radiochemistry
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