Label-Free Quantification of Pharmacokinetics in Skin with Stimulated Raman Scattering Microscopy and Deep Learning

Evaluation of chemical disposition in skin by stimulated Raman scattering microscopy

Tracking drug disposition in the skin in a non-destructive and at least semi-quantitative fashion is a relevant objective for the assessment of local (cutaneous) bioavailability. Confocal Raman spectroscopy has been shown potentially useful in this regard and, importantly, recent advances have enabled the presence of applied chemicals in the viable epidermis below the stratum corneum (SC) to be determined without ambiguity and having addressed the challenges of (a) background signals from endogenous species and noise and (b) signal attenuation due to absorption and scattering. This study aimed to confirm these observations using a different vibrational spectroscopy approach - specifically, stimulated Raman scattering (SRS) microscopy - and the more conventional in vitro skin penetration test (IVPT). SRS is a nonlinear optical imaging technique which enables more precise location of the skin surface and enhanced skin depth resolution relative to confocal Raman microscopy. The method can also probe larger areas of the sample under investigation and identify the localization of the permeating chemical in specific structural components of the skin. Here, SRS was shown capable of tracking the uptake and distribution of 4-cyanophenol (CP), the same model compound used in the recent confocal Raman investigation, at depths beyond the SC following skin treatment with different vehicles and for different times. The SRS results correlated well with those from the confocal Raman experiments, and both were consistent with independent IVPT measurements. Acquired images clearly delineated CP preference for the intercellular lipid layers of the SC relative to the corneocytes. The stage is now set to apply these and other correlative techniques to examine commercial drug products.

Determining topical product bioequivalence with stimulated Raman scattering microscopy

Generic drugs are essential for affordable medicine and improving accessibility to treatments. Bioequivalence (BE) is typically demonstrated by assessing a generic product's pharmacokinetics (PK) relative to a reference-listed drug (RLD). Accurately estimating cutaneous PK (cPK) at or near the site of action can be challenging for locally acting topical products. Certain cPK approaches are available for assessing local bioavailability (BA) in the skin. Stimulated Raman scattering (SRS) microscopy has unique capabilities enabling continuous, high spatial and temporal resolution and quantitative imaging of drugs within the skin. In this paper, we developed an approach based on SRS and a polymer-based standard reference for the evaluation of topical product BA and BE in human skin ex vivo. BE assessment of tazarotene-containing formulations was achieved using cPK parameters obtained within different skin microstructures. The establishment of BE between the RLD and an approved generic product was successfully demonstrated. Interestingly, within the constraints of the current study design the results suggest similar BA between the tested gel formulation and the reference cream formulation, despite the differences in the formulation/dosage form. Another formulation containing polyethylene glycol as the vehicle was demonstrated to be not bioequivalent to the RLD. Compared to using the SRS approach without a standard reference, the developed approach enabled more consistent and reproducible results, which is crucial in BE assessment. The abundant information from the developed approach can help to systematically identify key areas of study design that will enable a better comparison of topical products and support an assessment of BE.

Quantitative analysis of drug tablet aging by fast hyper-spectral stimulated Raman scattering microscopy

Pharmaceutical development of solid-state formulations requires testing active pharmaceutical ingredients (API) and excipients for uniformity and stability. Solid-state properties such as component distribution and grain size are crucial factors that influence the dissolution profile, which greatly affect drug efficacy and toxicity, and can only be analyzed spatially by chemical imaging (CI) techniques. Current CI techniques such as near infrared microscopy and confocal Raman spectroscopy are capable of high chemical and spatial resolution but cannot achieve the measurement speeds necessary for integration into the pharmaceutical production and quality assurance processes. To fill this gap, we demonstrate fast chemical imaging by epi-detected sparse spectral sampling stimulated Raman scattering to quantify API and excipient degradation and distribution.

Confocal Raman Spectroscopic Characterization of Dermatopharmacokinetics Ex Vivo

Confocal Raman spectroscopy is being assessed as a tool with which to quantify the rate and extent of drug uptake to and its clearance from target sites of action within the viable epidermis below the skin's stratum corneum (SC) barrier. The objective of this research was to confirm that Raman can interrogate drug disposition within the living layers of the skin (where many topical drugs elicit their pharmacological effects) and to identify procedures by which Raman signal attenuation with increasing skin depth may be corrected and normalized so that metrics descriptive of topical bioavailability may be identified. It was first shown in experiments on skin cross-sections parallel to the skin surface that the amide I signal, originating primarily from keratin, was quite constant with depth into the skin and could be used to correct for signal attenuation when confocal Raman data were acquired in a "top-down" fashion. Then, using 4-cyanophenol (CP) as a model skin penetrant with a strong Raman-active C≡N functionality, a series of uptake and clearance experiments, performed as a function of time, demonstrated clearly that normalized spectroscopic data were able to detect the penetrant to at least 40-80 μm into the skin and to distinguish the disposition of CP from different vehicles. Metrics related to local bioavailability (and potentially bioequivalence) included areas under the normalized C≡N signal versus depth profiles and elimination rate constants deduced post-removal of the formulations. Finally, Raman measurements were made with an approved dermatological drug, crisaborole, for which delivery from a fully saturated formulation into the skin layers just below the SC was detectable.

Optical Methods for Non-Invasive Determination of Skin Penetration: Current Trends, Advances, Possibilities, Prospects, and Translation into In Vivo Human Studies

Information on the penetration depth, pathways, metabolization, storage of vehicles, active pharmaceutical ingredients (APIs), and functional cosmetic ingredients (FCIs) of topically applied formulations or contaminants (substances) in skin is of great importance for understanding their interaction with skin targets, treatment efficacy, and risk assessment-a challenging task in dermatology, cosmetology, and pharmacy. Non-invasive methods for the qualitative and quantitative visualization of substances in skin in vivo are favored and limited to optical imaging and spectroscopic methods such as fluorescence/reflectance confocal laser scanning microscopy (CLSM); two-photon tomography (2PT) combined with autofluorescence (2PT-AF), fluorescence lifetime imaging (2PT-FLIM), second-harmonic generation (SHG), coherent anti-Stokes Raman scattering (CARS), and reflectance confocal microscopy (2PT-RCM); three-photon tomography (3PT); confocal Raman micro-spectroscopy (CRM); surface-enhanced Raman scattering (SERS) micro-spectroscopy; stimulated Raman scattering (SRS) microscopy; and optical coherence tomography (OCT). This review summarizes the state of the art in the use of the CLSM, 2PT, 3PT, CRM, SERS, SRS, and OCT optical methods to study skin penetration in vivo non-invasively (302 references). The advantages, limitations, possibilities, and prospects of the reviewed optical methods are comprehensively discussed. The ex vivo studies discussed are potentially translatable into in vivo measurements. The requirements for the optical properties of substances to determine their penetration into skin by certain methods are highlighted.

Measurement of chemical penetration in skin using Stimulated Raman scattering microscopy and multivariate curve resolution - alternating least squares

The mechanistic understanding of skin penetration underpins the design, efficacy and risk assessment of many high-value products including functional personal care products, topical and transdermal drugs. Stimulated Raman scattering (SRS) microscopy, a label free chemical imaging tool, combines molecular spectroscopy with submicron spatial information to map the distribution of chemicals as they penetrate the skin. However, the quantification of penetration is hampered by significant interference from Raman signals of skin constituents. This study reports a method for disentangling exogeneous contributions and measuring their permeation profile through human skin combining SRS measurements with chemometrics. We investigated the spectral decomposition capability of multivariate curve resolution - alternating least squares (MCR-ALS) using hyperspectral SRS images of skin dosed with 4-cyanophenol. By performing MCR-ALS on the fingerprint region spectral data, the distribution of 4-cyanophenol in skin was estimated in an attempt to quantify the amount permeated at different depths. The reconstructed distribution was compared with the experimental mapping of CN, a strong vibrational peak in 4-cyanophenol where the skin is spectroscopically silent. The similarity between MCR-ALS resolved and experimental distribution in skin dosed for 4 h was 0.79 which improved to 0.91 for skin dosed for 1 h. The correlation was observed to be lower for deeper layers of skin where SRS signal intensity is low which is an indication of low sensitivity of SRS. This work is the first demonstration, to the best of our knowledge, of combining SRS imaging technique with spectral unmixing methods for direct observation and mapping of the chemical penetration and distribution in biological tissues.

Multiphoton intravital microscopy of rodents

Tissues are heterogeneous with respect to cellular and non-cellular components and in the dynamic interactions between these elements. To study the behaviour and fate of individual cells in these complex tissues, intravital microscopy (IVM) techniques such as multiphoton microscopy have been developed to visualize intact and live tissues at cellular and subcellular resolution. IVM experiments have revealed unique insights into the dynamic interplay between different cell types and their local environment, and how this drives morphogenesis and homeostasis of tissues, inflammation and immune responses, and the development of various diseases. This Primer introduces researchers to IVM technologies, with a focus on multiphoton microscopy of rodents, and discusses challenges, solutions and practical tips on how to perform IVM. To illustrate the unique potential of IVM, several examples of results are highlighted. Finally, we discuss data reproducibility and how to handle big imaging data sets.

Raman Spectroscopic Tools to Probe the Skin-(Trans)dermal Formulation Interface

Medicines designed to deliver the active pharmaceutical ingredient either into or through the skin─often referred to as topicals and transdermals, respectively─are generally considered to be complex drug products. A particular challenge faced by these formulations is identifying a suitable method (ideally, in terms of specificity, accuracy, precision, and robustness) or combination of methods with which to assess the amount and rate of drug delivery to the target site. Significant research currently aims to identify and validate relevant and minimally invasive techniques that can be used to quantify both the levels of the drug attained within different parts of the skin and the kinetics with which the drug is taken up into the skin and cleared therefrom into the systemic circulation. Here, the application of confocal Raman microspectroscopy and imaging to interrogate events integral to the performance of topical and transdermal drug products at the formulation-skin interface is illustrated. Visualization, depth slicing, and profiling are used (a) to elucidate key chemical properties of both the delivery system and the skin that have impact on their interaction and the manner in which drug transfer from one to the other may occur, (b) for the transformation of a drug product from that manufactured into a residual phase post-application and inunction into the skin (including the potential for important changes in solubility of the active compound), and (c) for drug absorption into the skin and its subsequent '"clearance" into deeper layers and beyond. Overall, the Raman tools described offer both qualitative and potentially semi-quantitative insights into topical and transdermal drug product performance and provide information useful for formulation improvement and optimization.

Data-Driven Identification of Biomarkers for In Situ Monitoring of Drug Treatment in Bladder Cancer Organoids

Three-dimensional (3D) organoid culture recapitulating patient-specific histopathological and molecular diversity offers great promise for precision medicine in cancer. In this study, we established label-free imaging procedures, including Raman microspectroscopy (RMS) and fluorescence lifetime imaging microscopy (FLIM), for in situ cellular analysis and metabolic monitoring of drug treatment efficacy. Primary tumor and urine specimens were utilized to generate bladder cancer organoids, which were further treated with various concentrations of pharmaceutical agents relevant for the treatment of bladder cancer (i.e., cisplatin, venetoclax). Direct cellular response upon drug treatment was monitored by RMS. Raman spectra of treated and untreated bladder cancer organoids were compared using multivariate data analysis to monitor the impact of drugs on subcellular structures such as nuclei and mitochondria based on shifts and intensity changes of specific molecular vibrations. The effects of different drugs on cell metabolism were assessed by the local autofluorophore environment of NADH and FAD, determined by multiexponential fitting of lifetime decays. Data-driven neural network and data validation analyses (k-means clustering) were performed to retrieve additional and non-biased biomarkers for the classification of drug-specific responsiveness. Together, FLIM and RMS allowed for non-invasive and molecular-sensitive monitoring of tumor-drug interactions, providing the potential to determine and optimize patient-specific treatment efficacy.

Quantitative Stimulated Raman Scattering Microscopy: Promises and Pitfalls

Since its first demonstration, stimulated Raman scattering (SRS) microscopy has become a powerful chemical imaging tool that shows promise in numerous biological and biomedical applications. The spectroscopic capability of SRS enables identification and tracking of specific molecules or classes of molecules, often without labeling. SRS microscopy also has the hallmark advantage of signal strength that is directly proportional to molecular concentration, allowing for in situ quantitative analysis of chemical composition of heterogeneous samples with submicron spatial resolution and subminute temporal resolution. However, it is important to recognize that quantification through SRS microscopy requires assumptions regarding both system and sample. Such assumptions are often taken axiomatically, which may lead to erroneous conclusions without proper validation. In this review, we focus on the tacitly accepted, yet complex, quantitative aspect of SRS microscopy. We discuss the various approaches to quantitative analysis, examples of such approaches, challenges in different systems, and potential solutions. Through our examination of published literature, we conclude that a scrupulous approach to experimental design can further expand the powerful and incisive quantitative capabilities of SRS microscopy.

Research Progress of Raman Spectroscopy and Raman Imaging in Pharmaceutical Analysis

The analytical investigation of the pharmaceutical process monitors the critical process parameters of the drug, beginning from its development until marketing and postmarketing, and appropriate corrective action can be taken to change the pharmaceutical design at any stage of the process. Advanced analytical methods, such as Raman spectroscopy, are particularly suitable for use in the field of drug analysis, especially for qualitative and quantitative work, due to the advantages of simple sample preparation, fast, nondestructive analysis speed, and effective avoidance of moisture interference. Advanced Raman imaging techniques have gradually become a powerful alternative method for monitoring changes in polymorph distribution and active pharmaceutical ingredient distribution in drug processing and pharmacokinetics. Surface-enhanced Raman spectroscopy (SERS) has also solved the inherent insensitivity and fluorescence problems of Raman, which has made good progress in the field of illegal drug analysis. This review summarizes the application of Raman spectroscopy and imaging technology, which are used in the qualitative and quantitative analysis of solid tablets, quality control of the production process, drug crystal analysis, illegal drug analysis, and monitoring of drug dissolution and release in the field of drug analysis in recent years.

Yes SIR! On the structure-inactivity relationships in drug discovery

In analogy with structure-activity relationships (SARs), which are at the core of medicinal chemistry, studying structure-inactivity relationships (SIRs) is essential to understanding and predicting biological activity. Current computational methods should predict or distinguish 'activity' and 'inactivity' with the same confidence because both concepts are complementary. However, the lack of inactivity data, in particular in the public domain, limits the development of predictive models and its broad application. In this review, we encourage the scientific community to disclose and analyze high-confidence activity data considering both the labeled 'active' and 'inactive' compounds.

Visualizing Lipid Dynamics Role in Infrared Neural Stimulation using Stimulated Raman Scattering

Infrared neural stimulation, or INS, uses pulsed infrared light to yield label-free neural stimulation with broad experimental and translational utility. Despite its robust demonstration, INS's mechanistic and biophysical underpinnings have been the subject of debate for more than a decade. The role of lipid membrane thermodynamics appears to play an important role in how fast IR-mediated heating nonspecifically drives action potential generation. Direct observation of lipid membrane dynamics during INS remains to be shown in a live neural model system. We used hyperspectral stimulated Raman scattering (hsSRS) microscopy to study biochemical signatures of high-speed vibrational dynamics underlying INS in a live neural cell culture model. Findings suggest that lipid bilayer structural changes are occurring during INS in vitro in NG108-15 neuroglioma cells. Lipid-specific signatures of cell SRS spectra varied with stimulation energy and radiant exposure. Spectroscopic observations agree with high-speed ratiometric fluorescence imaging of a conventional lipophilic membrane structure reporter, di-4-ANNEPS. Overall, the presented findings support the hypothesis that INS causes changes in the lipid membrane of neural cells by changing lipid membrane packing order. Furthermore, this work highlights the potential of hsSRS as a method to study biophysical and biochemical dynamics safely in live cells.

A Neural Network-Based Method for Fast Capture and Tracking of Laser Links between Nonorbiting Platforms

In this paper, a neural network approach is used to conduct an in-depth study and analysis of the fast capture tracking method for laser links between nonorbiting platforms. The experimental platform of the convolutional neural network- (CNN-) based free-space optical communication (FSO) wavefront correction system is built indoors, and the wavefront distortion correction performance of the CNN-based wavefront correction method is investigated. The experimental results show that the coupling power loss can be reduced to small after the CNN method correction under weak and strong turbulence. The accuracy of the above model is verified by comparing the simulation data with the experimentally measured data, thus realizing the coordinate decoupling of the coarse aiming mechanism and weakening the influence of structural factors on the tracking accuracy of the system. The tracking correlation equation of the influence of beam far-field dynamic characteristics on the tracking stability of the link is established, and the correlation factor variance of beam far-field dynamic characteristics is used to provide a quantitative analysis method for the evaluation and prediction of the comprehensive performance of the link tracking stability. The influence of beam divergence angle, wavefront distortion, detector accuracy, and atmospheric turbulence disturbance on the correlation factor variance of beam far-field dynamic characteristics of laser link beacons is modelled, and the link tracking stability optimization method is proposed under the requirement of link tracking accuracy, which provides an effective solution analysis method to realize the improvement of laser link tracking stability.

Applications of machine learning in computer-aided drug discovery

Machine learning (ML) has revolutionised the field of structure-based drug design (SBDD) in recent years. During the training stage, ML techniques typically analyse large amounts of experimentally determined data to create predictive models in order to inform the drug discovery process. Deep learning (DL) is a subfield of ML, that relies on multiple layers of a neural network to extract significantly more complex patterns from experimental data, and has recently become a popular choice in SBDD. This review provides a thorough summary of the recent DL trends in SBDD with a particular focus on de novo drug design, binding site prediction, and binding affinity prediction of small molecules.

Visualizing and quantifying antimicrobial drug distribution in tissue

The biodistribution and pharmacokinetics of drugs are vital to the mechanistic understanding of their efficacy. Measuring antimicrobial drug efficacy has been challenging as plasma drug concentration is used as a surrogate for tissue drug concentration, yet typically does not reflect that at the intended site(s) of action. Utilizing an image-guided approach, it is feasible to accurately quantify the biodistribution and pharmacokinetics within the desired site(s) of action. We outline imaging modalities used in visualizing drug distribution with examples ranging from in vitro cellular drug uptake to clinical treatment of microbial infections. The imaging modalities of interest are: radio-labeling, magnetic resonance, mass spectrometry imaging, computed tomography, fluorescence, and Raman spectroscopy. We outline the progress, limitations, and future outlook for each methodology. Further advances in these optical approaches would benefit patients and researchers alike, as non-invasive imaging could yield more profound insights with a lower clinical burden than invasive measurement approaches used today.

Automated Extraction of Skin Wound Healing Biomarkers From In Vivo Label-Free Multiphoton Microscopy Using Convolutional Neural Networks

BACKGROUND AND OBJECTIVES

Histological analysis is a gold standard technique for studying impaired skin wound healing. Label-free multiphoton microscopy (MPM) can provide natural image contrast similar to histological sections and quantitative metabolic information using NADH and FAD autofluorescence. However, MPM analysis requires time-intensive manual segmentation of specific wound tissue regions limiting the practicality and usage of the technology for monitoring wounds. The goal of this study was to train a series of convolutional neural networks (CNNs) to segment MPM images of skin wounds to automate image processing and quantification of wound geometry and metabolism.

STUDY DESIGN/MATERIALS AND METHODS

Two CNNs with a 4-layer U-Net architecture were trained to segment unstained skin wound tissue sections and in vivo z-stacks of the wound edge. The wound section CNN used 380 distinct MPM images while the in vivo CNN used 5,848 with both image sets being randomly distributed to training, validation, and test sets following a 70%, 20%, and 10% split. The accuracy of each network was evaluated on the test set of images, and the effectiveness of automated measurement of wound geometry and optical redox ratio were compared with hand traced outputs of six unstained wound sections and 69 wound edge z-stacks from eight mice.

RESULTS

The MPM wound section CNN had an overall accuracy of 92.83%. Measurements of epidermal/dermal thickness, wound depth, wound width, and % re-epithelialization were within 10% error when evaluated on six full wound sections from days 3, 5, and 10 post-wounding that were not included in the training set. The in vivo wound z-stack CNN had an overall accuracy of 89.66% and was able to isolate the wound edge epithelium in z-stacks from eight mice across post-wound time points to quantify the optical redox ratio within 5% of what was recorded by manual segmentations.

CONCLUSION

The CNNs trained and presented in this study can accurately segment MPM imaged wound sections and in vivo z-stacks to enable automated and rapid calculation of wound geometry and metabolism. Although MPM is a noninvasive imaging modality well suited to imaging living wound tissue, its use has been limited by time-intensive user segmentation. The use of CNNs for automated image segmentation demonstrate that it is possible for MPM to deliver near real-time quantitative readouts of tissue structure and function. Lasers Surg. Med. © 2021 Wiley Periodicals LLC.

Multi-window sparse spectral sampling stimulated Raman scattering microscopy

Stimulated Raman scattering (SRS) is a nondestructive and rapid technique for imaging of biological and clinical specimens with label-free chemical specificity. SRS spectral imaging is typically carried out either via broadband methods, or by tuning narrowband ultrafast light sources over narrow spectral ranges thus specifically targeting vibrational frequencies. We demonstrate a multi-window sparse spectral sampling SRS (S4RS) approach where a rapidly-tunable dual-output all-fiber optical parametric oscillator is tuned into specific vibrational modes across more than 1400 cm-1 during imaging. This approach is capable of collecting SRS hyperspectral images either by scanning a full spectrum or by rapidly tuning into select target frequencies, hands-free and automatically, across the fingerprint, silent, and high wavenumber windows of the Raman spectrum. We further apply computational techniques for spectral decomposition and feature selection to identify a sparse subset of Raman frequencies capable of sample discrimination. Here we have applied this novel method to monitor spatiotemporal dynamic changes of active pharmaceutical ingredients in skin, which has particular relevance to topical drug product delivery.

Coherent Raman Scattering Microscopy in Oncology Pharmacokinetic Research

The high attrition rates of anti-cancer drugs during clinical development remains a bottleneck problem in pharmaceutical industry. This is partially due to the lack of quantitative, selective, and rapid readouts of anti-cancer drug activity in situ with high resolution. Although fluorescence microscopy has been commonly used in oncology pharmacological research, fluorescent labels are often too large in size for small drug molecules, and thus may disturb the function or metabolism of these molecules. Such challenge can be overcome by coherent Raman scattering microscopy, which is capable of chemically selective, highly sensitive, high spatial resolution, and high-speed imaging, without the need of any labeling. Coherent Raman scattering microscopy has tremendously improved the understanding of pharmaceutical materials in the solid state, pharmacokinetics of anti-cancer drugs and nanocarriers in vitro and in vivo. This review focuses on the latest applications of coherent Raman scattering microscopy as a new emerging platform to facilitate oncology pharmacokinetic research.