A new revision to the U.S. Food and Drug Administration (FDA)’s 

Compliance Program Guide for Pre-Approval Inspections 

(PAIs) has added a fourth objective: Commitment to Quality in Pharmaceutical Development. PAIs are going to be very interesting now.....

Compliance Program Guide for Pre-Approval Inspections (PAIs)

 has added a fourth objective: Commitment to Quality in Pharmaceutical Development. PAIs are going to be very interesting now.....

Spectroscopists usually consider chromatography as sample cleanup for their analysis. However, all spectroscopists working in regulated laboratories are living with the fallout of the 2005 fraud perpetrated by the chromatographers at Able Laboratories. The problem was that the Food and Drug Administration (FDA) had carried out seven pre-approval inspections (PAIs) of Able Laboratories, and they had not found any compliance problems until a whistleblower informed them of the compliance issues.

After a two-month inspection by four inspectors, a 483 was issued (1), and the FDA withdrew all product licenses that triggered a recall of over 3100 batches, resulting in Able’s bankruptcy.

The problem for the FDA was that inspectors focused only on paper printouts—not electronic records during the seven PAIs. Reading the 483, you’ll see how the chromatography data system audit trail aided the inspectors (1). The FDA’s response was to issue a revision of 

 to become effective in 2012 after inspector training. This had three objectives:

Although data integrity runs through all three, it is the third objective where
inspectors should look to see if there was a laboratory data integrity problem.

(CPG) was updated (3), with more emphasis in Objective 3 on laboratory data integrity violations that had been identified since 2010, and this was discussed in a previous “Focus on Quality” column (4). During a PAI, there will be an inspection focus on research and development (R&D) with the documentation and data used to support the product license application inspected under Objectives 2 and 3. Technology transfer to Quality Control is also within scope, as well as any analysis performed for registration purposes.

Living in London, we have an expression—”Wait all day for a bus, and three turn up at once.” Here’s the FDA equivalent: in October 2022, the FDA issued another update to 

(5). Connoisseurs of FDA know that the time between the issue of a draft and final (or more likely another draft) guidance document can be glacial, but three final versions of 

 in 12 years qualifies for the bus comment.

New Objective 4: Quality in Pharmaceutical Development

As mentioned in the abstract, the main change in the latest version is the addition of a fourth objective to 

: Commitment to Quality in Pharmaceutical Development. “Pharm Development” 

and “Quality” mentioned in the same sentence? Is this a contradiction?

Assess the pharmaceutical development program by evaluating the extent to which it is supported, defined, managed and continually assessed for its effectiveness as well as its use in supporting continual improvement of the Pharmaceutical Quality System (PQS) (5).

What does this mean in practice? The PQS, pharmaceutical development, and continual improvement are mentioned. However, this is within the context of the overall CPG, where one overarching aim is to ensure that data in a regulatory submission is accurate, complete, and consistent, and not been cherry picked. To put this in context, we need to consider the Data Integrity Model (6,7), shown in Figure 1.

An earlier “Focus on Quality” column, and related publication, discussed a data integrity model within a Pharmaceutical Quality System (PQS) that consisted of a foundation and three levels involving qualification and validation of instruments and systems, validation of methods and application of all to the analysis of samples (6,7). In addition, there must be QA oversight of all work (Figure 1). Objective 4 can be mapped to the foundation level of the model that is essentially data governance:

Data integrity procedures with effective training

The goal is to find the right people and approach to do the job. If an organization can’t get these fundamentals right, we end up with another Able Laboratories.

The CPG breaks down Objective 4 down into four areas that are indicative of an organization’s commitment to quality in pharmaceutical development and shown in Table I. The four areas are:

Multidisciplinary Integrated Development Team

Objective 4 reflects the integration of the principles of 

(9) into FDA PAIs. This is a good example why any regulated organization must keep current.

The aim of pharmaceutical development is to design a quality product and its manufacturing process to consistently deliver the intended performance of the product [8].

This means development of a manufacturing process, the product formulation, and all associated analytical procedures covering raw materials, in-process samples, and finished product analysis.

We’ll discuss two aspects of Objective 4 here:

Technology transfer of analytical procedure from Analytical Development to Quality Control.

Management leadership in the foundation layer of the Data integrity Model in Figure 1 is the key to data integrity and quality success. What is expected of senior management? From a data integrity perspective, the 2018 FDA guidance is very explicit:

Meaningful and effective strategies should consider the design, operation, and monitoring of systems and controls based on risk to patient, process, and product. Management’s involvement in and influence on these strategies is essential in preventing and correcting conditions that can lead to data integrity problems.

It is the role of management with executive responsibility to create a quality culture where employees understand that data integrity is an organizational core value and employees are encouraged to identify and promptly report data integrity issues. In the absence of management support of a quality culture, quality systems can break down and lead to CGMP non-compliance (10).

This data integrity expectation of FDA is then rolled into the scope and intent of Objective 4 in the 

Assess the establishment’s ability to develop and manufacture drugs of consistent quality. This includes determining whether an establishment has implemented and follows a development program that applies sound science and principles of material science, engineering, knowledge management, and quality risk management in a holistic manner (5).

Senior management does not escape the responsibility for the PQS under E

Senior management has the ultimate responsibility to ensure an effective Pharmaceutical Quality System is in place, adequately resourced, and that roles, responsibilities, and authorities are defined, communicated and implemented throughout the organization. Senior management’s leadership and active participation in the Pharmaceutical Quality System is essential. This leadership should ensure the support and commitment of staff at all levels and sites within the organization to the Pharmaceutical Quality System (11).

Thus, senior management can make or break integrity and quality.

At Able Laboratories (1), senior management had an expectation that all product batches would meet specifications—or you’re fired. How’s that for an incentive to bend the rules? Recently, intense management and investor pressure on research staff at vaccine startup Laronde led to data falsification and the inability to replicate experiments, resulting in cancellation of two late-stage research projects (12). An R&D version of Able Laboratories
without the heavy plod of FDA footsteps!

Technology Transfer of Analytical Procedures

For the second area of Objective 4, we need to look at technology transfer. Stage left we have Analytical Development, who are responsible for developing and validating analytical procedures. Stage right we have Quality Control (QC), who have the dubious task of establishing a validated procedure and using it for routine analysis of production batches. Center stage, there is space to build a large wall between the two departments. The building of the wall is dependent on how the two departments communicate for technology transfer. No wall equals much communication; high wall…...

Is QC consulted on the development of the procedure?

How is the analytical procedure communicated? Throw the report over the wall and let QC get on with it? Are there discussions with QC and their involvement in the development and validation?

Are equivalent instruments available in both departments to ease the transfer?

Are Analytical Development’s spectrometers qualified to the same parameters used in QC? Indeed, are they qualified at all?

Are the same data systems used in both Departments?

Why are these questions important? Let us return to the trigger for this column, 

…. comprehensive process and product understanding to the extent possible (5).

If there is no collaboration between the two departments, how can this information and knowledge be transferred to QC? Where is the commitment to quality required by Objective 4?

Table II compares the functions of analytical development and quality Control; the key to our discussion is the bottom row with the relationships for transfer and establishment of an analytical procedure in QC.

In an ideal world, technology transfer would be facilitated by using the same spectrometers and software so that the instrument methods can be transferred electronically with spectra. This would give the receiving laboratory more detail than is generally available in a written document. Rarely is it an ideal world, as R&D and Production have different budgets. There are two options for optimal transfer of analytical procedures:

Share the overall validation between the two departments. The main work is conducted by Analytical Development, but intermediate precision involves QC staff working with their instruments in their laboratories. Both departments are co-signatories of the final validation report.

A member of QC could work in the originating laboratory to learn and understand the procedure and speed establishment in their own laboratory, simplifying the transfer protocol.

Regardless of the transfer mechanism, how long should Analytical Development support QC after the procedure has been transferred? QC analysts may need access to development records, in case of situations where a procedure may need to be modified in the future. Ongoing data sharing and collaboration is critical for success.

, the frequency of inspecting Objective 4 is noted (5):

Periodically in subsequent PAIs, with the frequency based on risk

In addition, when there have been major changes to the quality system, management team or corporate structure (at the rate of change and merger in some organizations this can mean every PAI).

The depth of coverage during an inspection will vary based on the risk and application specific issues identified. To summarize, if you have been good boys and girls in a stable environment, then you’ll see less of an inspector for this objective. Otherwise, you could be on first name terms….

The publication of a new FDA compliance policy for PAIs brings a new area for inspection: quality in pharmaceutical development. Senior management are responsible for ensuring the culture and ethos in R&D, and should not apply pressure on staff or data integrity suffers. Communication and involvement in analytical procedure validation and transfer between Analytical Development and QC is critical for success.

(1) Able Laboratories Form 483 Observations. 2005; Available from: 

 Compliance Program Guide CPG 7346.832 Pre-Approval Inspections

. 2010, Food and Drug Adminsitration: Silver Spring, Maryland.

 Compliance Program Guide CPG 7346.832 Pre-Approval Inspections.

 2019, Food and Drug Administration: Silver Spring, Maryland.

(4) McDowall, R. D. Do You Understand the FDA’s Updated Approach to Pre-Approval Inspections? 

 2022, Food and Drug Administration: Silver Spring. Maryland.

(6) McDowall, R. D. Understanding the Layers of a Laboratory Data Integrity Model. 

Data Integrity and DataGovernance: Practical Implementation in Regulated Laboratories; R

. 2009, International Council on Harmonisation: Geneva, Switzerland.

2023, International Council for Harmonisation: Geneva, Switzerland.

 FDA Guidance for Industry Data Integrity and Compliance With Drug CGMP Questions and Answers

 2018, Food and Drug Administration: Silver Spring, Maryland.

 EudraLex - Volume 4 Good Manufacturing Practice (GMP) Guidelines, Chapter 1 Pharmaceutical Quality System

. 2013, European Commission: Brussels, Belgium.

(12) DeAngelis, A.; Cross, R. The Inside Story of How Data Integrity Issues Roiled a Biotech Seen as “Moderna 2.0.” 

https://www.statnews.com/2023/06/12/laronde-data-integrity-issues-biotech/

Articles

Columns: Focus on Quality

The publication of a new FDA compliance policy for pre-approval inspections (PAIs) introduces a new objective to inspect research and development in 
pharmaceutical development. We explore how this could influence the PAI process now.

Guess Who’s Coming  to Inspect R&D?

Almost all of the compounds whose spectra we have discussed so far in this column series have contained carbon, hydrogen, oxygen, and nitrogen only. However, there are a number of important compounds that contain other
elements that are still considered organic, such as halogenated organics. In this column, we will discuss the spectra of halogenated compounds generally, then specifically discuss the spectra of some common halogenated polymers.

Almost all of the compounds whose spectra we have discussed so far in this column series have contained carbon, hydrogen, oxygen, and nitrogen only. However, there are a number of important compounds that contain other elements that are still considered organic, such as halogenated organics. In this column, we will discuss the spectra of halogenated compounds generally, then specifically discuss the spectra of some common halogenated polymers.

This review may seem ridiculously basic for a magazine perused by chemists and physicists, but bear with me here, as a refresher has never hurt anybody. The current form of the Periodic Table of the Chemical Elements is seen in Figure 1. The table is periodic because the properties of the chemical elements repeat themselves. For example, the left-most column containing lithium, sodium, and potassium, otherwise known as the alkali metals (hydrogen is a special case and will be ignored here), are all shiny reactive metals at room temperature that tend to give up electrons during chemical reactions and form ions with a +1 charge. In the Periodic Table, the elements to the left and below are metals, and the elements to the right and above are non-metals. So far, in the many years I have been writing this column,
almost all the compounds we have discussed were organics and contained the non-metals carbon, hydrogen, nitrogen, and oxygen.

Note that to the far right of the periodic table, there is a column of elements containing fluorine, chlorine, bromine, and iodine. These are called the 

 from the Greek words for “salt forming.” Halogens tend to gain electrons during chemical reactions and are normally quite electronegative. The most electronegative element, fluorine, is a halogen. Our focus here will be the first four members of the halogen family – fluorine, chlorine, bromine, and iodine – because they are the halogens most commonly found in organic compounds.

Halogenated Organics and Their Infrared Spectra

Carbon forms stable bonds with fluorine (F), chlorine (Cl), bromine (Br), and iodine (I). In the ensuing discussion, I will sometimes use the letter “X” to stand for any or all of these four elements. Thus, the phrase “C-X bonds” refers to C-F, C-Cl, C-Br, and C-I bonds. The atomic masses of these four elements, rounding for simplicity, are fluorine at 19, chlorine at 35, bromine at 80, and iodine at 127. Recall (1) that the peak positions in infrared spectra depend upon force constant and atomic mass, as given by equation 1:

 equals reduced mass, as given by equation 2:

equals mass of atom 1 in a chemical bond, and 

 equals mass of atom 2 in a chemical bond.

Note in equation 1 that reduced mass is in the denominator, so as the mass of the atoms in a chemical bond goes up, peak position goes down, which we have referred to before as a 

(1). This phenomenon should then hold true for C-X bonds; we would expect the C-X stretching vibration peak positions to go in the order C-F > C-Cl >C-Br > C-I. This turns out to be true, as illustrated by the spectra in Figure 2.

The spectra in Figure 2 from top to bottom are of polytetrafluoroethylene (Teflon) or [CF

 in red. The spectra displayed have been expanded to show the 1300 to 500 cm

 region.
These four spectra are good examples, as each of them contains the CX

Note that the spectra are in order of increasing halogen mass from top to bottom. As we go from a C-F stretch at the top to a C-I stretch at the bottom, we see that Teflon’s C-F stretch is at 1154 cm

 (all peak position going forward will be in cm

, even if not so noted), methylene chloride’s C-Cl stretch is at 739, methylene bromide’s C-Br stretch is at 639, and methylene iodide’s C-I stretch is at 570. Thus, C-X stretches obey equation 1; as the atomic mass of the halogen goes up, the peak position goes down.

The spectrum of the common halogenated solvent chloroform is seen in Figure 3. The C-Cl stretch here is at 758, similar to that of CH

 at 739. Chloroform is a common organic solvent, and was one of the first substances ever used as an anesthetic.

Note from Figure 2 that all C-X stretches are at relatively low wavenumbers. Note from Figure 3 that the C-Cl stretch here is quite intense. Recall (1) that infrared peak intensities depend upon (d

, the change in dipole moment with respect to distance during a vibration. C-X stretches are generally intense because C-X bonds tend to have large dipole moments due to the electronegativity differences between carbon and the halogens.

Table I shows the peak position ranges for C-X stretches. The good news in Table I is that C-X stretching ranges follow equation 1 as expected, with the C-X stretching peak position ranges going down as halogen mass goes up. However, the bad news is that there is significant overlap in some of the ranges in Table I. Specifically, if a C-X stretch falls between 650 and 600, it could be from a C-Cl or C-Br bond, and if a C-X stretch falls between 570 and 550, it could be a C-Br or C-I bond. In a perfect world, Table I would be unambiguous, and we could use C-X stretches to tell us what halogen is present in an organic compound. As it turns out, Table I works sometimes, but not all of the time. This occasionally limits our ability to determine the halogens present in a sample from infrared spectroscopy by itself. In cases where Table I is ambiguous, other analytical methods such as mass spectrometry may be needed to determine the halogens present in a halogenated organic compound.

The last 13 columns (2–14) have been devoted to the infrared spectra of polymers. It has taken us almost three years to cover this topic.
This is justified because, in my experience, the analysis of polymers is the most common application of infrared spectroscopy (15). However, it is about time to wrap up the “analysis of polymers” topic. I present here what will be the last spectra of polymers we will discuss, at least for a while.

Figure 4 shows the spectrum of polyvinylidene fluoride. This polymer is sold under tradenames Kynar and Hylar, and is made into wire coatings and durable paints. The C-F stretch for this polymer is seen at 1190, as noted in the figure. As is typical for a C-X stretch, this peak is intense and at a relatively low wavenumber.

The vitons are a family of elastomers that contain fluorine (16). Widely used as gaskets, sealants, and O-rings, the stability of the C-F bonds lends them good chemical resistance. The spectrum of a viton (in this case a co-polymer of tetrafluoroethylene and propylene) is seen in Figure 5. The series of peaks between 1200 and 1000 are assignable as C-F stretching vibrations.

As previously mentioned, every rule I teach about infrared spectral interpretation has exceptions. One of the best rules I have taught you is that saturated carbons, including methyl (CH

), and methine (C-H) groups have C-H stretching peaks below 3000 (17). I also stated that unsaturated carbons including alkenes (C=C), alkynes (C≡C), and aromatic rings have C-H stretching peaks above 3000 (17). This is where I make a liar out of myself. Take a look at Figure 6, which shows the infrared spectra of three compounds in Figure 2 (methylene chloride [CH

]), but expanded from 4000 to 400. The Teflon spectrum has been left out because it lacks C-H bonds. These compounds contain saturated carbons, yet methylene chloride has a C-H stretch at 3054, methylene bromide has one at 3065, and methylene iodide has one at 3046. Additionally, in Figure 3, chloroform has a C-H stretch at 3019, Figure 4 shows that vinylidene chloride also has a C-H stretch at 3019, and our viton polymer in Figure 5 has a C-H stretch at 3003.

What’s going on here? I wish I knew. My perusal of the literature has not yielded any satisfactory answers. It is possible that the presence of electron withdrawing groups, such as the halogens on a carbon atom, messes with the force constant of the C-H bonds attached to that carbon, thus altering the expected C-H stretching peak position.

In addition to C, H, N, and O, organic compounds can contain the highly electronegative elements that are the main halogens – fluorine (F), chlorine (Cl), bromine (Br), and iodine (I). The infrared spectra of carbon halogen or C-X bonds are characterized by intense and low wavenumber C-X stretching vibration peaks. The ranges for C-X stretching peaks go down as the mass of the halogen goes up, as seen in Table I. However, the ranges for some of these peaks overlap, sometimes limiting our ability to identify halogens in a compound by infrared spectroscopy alone. The presence of halogens on carbon atoms also containing C-H bonds can cause the C-H stretching peaks to appear higher than expected. It is possible that the presence of electron withdrawing groups such as the halogens on a carbon atom messes with the force constant of the C-H bonds attached to that carbon, thus altering the expected C-H stretching peak position.

(1) Smith, B. C. IR Spectral Interpretation Workshop. 

(2) Smith, B. C. The Infrared Spectra of Polymers, Part I: Introduction. 

(3) Smith, B. C. The Infrared Spectra of Polymers II: Polyethylene. 

 (9), 24–29. DOI: 10.56530/spectroscopy.xp7081p7

(4) Smith, B. C. The Infrared Spectra of Polymers III: Hydrocarbon Polymers. 

 (11), 22–25. DOI: 10.56530/spectroscopy.mh7872q7

(5) Smith, B. C. The Infrared Spectra of Polymers IV: Rubbers. 

 (1), 8–12. DOI: 10.56530/spectroscopy.mz6968v1

(6) Smith, B. C. The Infrared Spectra of Polymers V: Epoxies. 

37 (3), 17–19. DOI: 10.56530/spectroscopy.mg2473z4

(7) Smith, B. C. The Infrared Spectra of Polymers, VI: Polymers With C-O Bonds. 

(5), 15–19, 27. DOI: 10.56530/spectroscopy.ly3071f5

(8) Smith, B. C. The Infrared Spectra of Polymers, VII: Polymers with Carbonyl (C=O) Bonds. 

 (8), 10–13. DOI: 10.56530/spectroscopy.tz9280y5

(9) Smith, B. C. Infrared Spectroscopy of Polymers, VIII: Polyesters and the Rule of Three. 

 (10), 25–28. DOI: 10.56530/spectroscopy.ta9383e3

(10) Smith, B. C. Infrared Spectroscopy of Polymers, IX: Pendant Ester Polymers and Polycarbonates. 

 (11), 16–19, 31. DOI: 10.56530/spectroscopy.xn9369p8

(11) Smith, B. C. Infrared Spectroscopy of Polymers X: Polyacrylates. 

 (1), 10–14. DOI: 10.56530/spectroscopy.mi9381w4

(12) Smith, B. C. Infrared Spectroscopy of Polymers, XI: Introduction to Organic Nitrogen Polymers. 

 (3), 14–18. DOI: 10.56530/spectroscopy.vd3180b5

(13) Smith, B. C. Infrared Spectroscopy of Polymers XII: Polyaramids and Slip Agents. 

 (5), 16–18. DOI: 10.56530/spectroscopy.np7466n5

(14) Smith, B. C. Infrared Spectroscopy of Polymers XIII: Polyurethanes. 

 (7), 14–16. DOI: 10.56530/spectroscopy.fn3378a3

 Infrared Spectral Interpretation: A Systematic Approach;

(16) Viton High-Performance Fluoroelastomers. 

(17) Smith, B. C. The Infrared Spectroscopy of Alkenes. 

Column: IR Spectral Interpretation Workshop

An examination of halogenated compounds and some common halogenated polymers is explored here.

Halogenated Organic Compounds

This year’s Emerging Leader in Molecular Spectroscopy Award recipient is Dmitry Kurouski, an assistant professor of chemistry at the Texas A&M University in College Station, Texas. From his early research days as a graduate student at State University of New York in Albany, Kurouski’s research has emphasized the development and application of innovative Raman spectroscopy methods for noninvasive, nondestructive analyses of biological materials.

Dmitry Kurouski is an assistant professor of chemistry at Texas A&M University who has made significant contributions to the field of molecular spectroscopy. His groundbreaking work has earned him the 2023 Emerging Leader in Molecular Spectroscopy Award.

Kurouski’s research pioneered the development of innovative Raman spectroscopy–based sensing approaches that can be used for noninvasive, nondestructive analysis, including confirmatory diagnostics of biotic and abiotic stresses in plants. His findings demonstrate that Raman spectroscopy can be used for the identification of viral, fungal, and bacterial diseases in many plant species. He has also developed Raman methods for diagnostics of plant deficiencies in micro and macro element composition; his work has also demonstrated the potential for Raman spectroscopy–based phenotyping of plants.

 Magazine, recognizes the achievements and aspirations of a talented young molecular spectroscopist, with recipients being selected by an independent scientific committee. The award will be presented to Kurouski at the SciX 2023 conference held October 8–13 in Sparks, Nevada, where he will be honored in a symposium.

Using Raman Spectroscopy for Complex Applications

Kurouski received his PhD in 2013 from SUNY Albany, State University of New York, working with Professor Igor K. Lednev. While working on his PhD, Kurouski developed a deeper understanding of Raman spectroscopy for complex applications.

His early work has led to cutting-edge optical nanoscopic approaches that are based on tip-enhanced Raman spectroscopy (TERS) and atomic force microscopy (AFM) infrared (IR) imaging. His research group now utilizes this nano-Raman-nano-IR imaging approach to reveal the structural organization of amyloid oligomers and protein aggregates that are linked to many neurodegenerative diseases. He has also discovered that the structure and toxicity of amyloid oligomers can be uniquely altered by lipids. These findings suggest that irreversible changes in lipid profiles of organs may be the 

underlying biophysical cause that triggers formation of toxic protein species, which in turn are responsible for the onset and progression of amyloidogenic-type diseases. He was recently awarded a highly prestigious $1 million Maximizing Investigators’ Research Award (MIRA) from the National Institute of Health (NIH) to investigate the effect of lipids on the structure and toxicity of amyloid oligomers.

Kurouski and his research group have made significant progress in understanding the physics of hot carriers and plasmon-driven catalysis on mono- and bimetallic nanostructures. These findings discovered by his group have allowed for elucidation of the underlying physical cause of unique reactivity and selectivity in plasmon-driven catalysis, specifically on gold-platinum and gold-palladium bimetallic nanostructures.

Kurouski’s group developed and deployed Raman spectroscopy for diagnostics of structural and metabolic changes in plants that can be used for confirmatory detection and identification of abiotic stress. The researchers developed spectroscopic libraries that, together with a hand-held Raman spectrometer, could be used to detect and identify nitrogen, phosphorus, and potassium deficiencies in rice. It was also demonstrated that Raman spectroscopy can be used for pre-symptomatic diagnostics of medium and high salinity stress in plants. Together, with more than 40 research reports on this topic, this work showed the emerging potential of Raman spectroscopy in agriculture. These findings are summarized in a review published by the Kurouski group last year.

Kurouski and his research team also have used nano-Raman-nano-IR imaging approaches to unravel the structural organization of viruses. Kurouski found that TERS was capable of resolving protein secondary structure, charge profile, and amino acid composition of the viral capsid with sub-nanometer spatial resolution, providing unprecedented insights into the organization and properties of viruses. At the same time, AFM-IR allowed for the elucidation of structural organization of the nucleic acids in viruses. This work demonstrated the complementary measurements of AFM-IR and TERS in probing depth and chemical information for challenging applications. With the development of confirmatory approaches for highly accurate identification of viruses, Kurouski’s research has significant implications for improving diagnostics and treatment of viral diseases. His groundbreaking work in the field of molecular spectroscopy has already made a significant impact on the scientific community and has the potential to revolutionize many aspects of modern medicine and agriculture.

Applying SERS and TERS for Characterization of Biological Systems

In his early work, Kurouski and coworkers used surface- and tip-enhanced Raman spectroscopy (SERS and TERS) as powerful tools for structural characterization of biological systems at the single-molecule scale (1).
However, enhanced Raman spectra of biological specimens often lack the amide I band, which is commonly used as a marker for the interpretation of secondary protein structures.

, the authors investigate the cause of this phenomenon for native insulin and insulin fibrils using both TERS and SERS, comparing these spectra to the spectra of well-defined homo-peptides. The results show that the appearance of the amide I Raman band is not determined by the protein aggregation state, but rather by the size of the amino acid side chain. Peptides with small side chain groups exhibit an intense amide I band in almost all acquired spectra, whereas those with bulky side chains, such as tyrosine and tryptophan, exhibit 

the amide I band in only a fraction of the acquired spectra.

This work provides new insights into the interpretation of Raman spectra of biological specimens and has important implications for the application of SERS and TERS in the study of protein structure and aggregation. The findings have the potential to improve our understanding of protein folding and aggregation mechanisms, as well as aid in the development of new diagnostic tools for protein misfolding diseases.

The chemical composition of materials at the nanoscale can be challenging to analyze and understand using traditional analytical techniques. To address this issue, the integration of infrared (IR) and Raman spectroscopy with scanning probe methods has resulted in the development of new nanospectroscopy paradigms, such as photothermal induced resonance (PTIR), also known as AFM-IR, and tip-enhanced Raman spectroscopy (TERS). In an article published in 

, Kurouski and co-authors provide a detailed overview of the fundamentals and recent advances of AFM-IR and TERS, as well as complementary features (2).

The article highlights how the recent innovations in AFM-IR and TERS have expanded its applications in various fields, such as materials science, nanotechnology, biology, medicine, geology, optics, catalysis, and art conservation. Although AFM-IR and TERS were initially developed independently for different applications, the recent advancements have pushed its performance beyond initial expectations, making them spectroscopically complementary techniques. There are opportunities for these techniques to converge and complement each other, providing researchers with more insights into the chemical composition of materials at the nanoscale. AFM-IR and TERS have become crucial techniques for nanoscale chemical imaging and spectroscopy.

In another study by Lei Zhou and Kurouski, atomic force microscopy-infrared spectroscopy (AFM-IR) was used to examine the structure of individual α-synuclein oligomers at different stages of protein aggregation (3). The aggregation of α-synuclein protein is strongly linked to the development of Parkinson’s disease (PD). However, the structure and morphology of toxic intermediate oligomers formed during the aggregation process are not fully understood. The use of AFM-IR in this study allowed for the examination of individual oligomers at the nanoscale, which is critical for understanding the aggregation process and its relationship to protein structure.

Aberrant aggregation of α-synuclein protein is a hallmark of PD and other neurodegenerative disorders. The accumulation of α-synuclein in the form of intracellular inclusions, called Lewy bodies, is a pathological feature of PD. These inclusions are highly toxic to neurons, leading to neuronal dysfunction and degeneration. Additionally, soluble oligomeric forms of α-synuclein have been found to be highly neurotoxic and capable of inducing the formation of Lewy bodies. Therefore, understanding the structure and properties of α-synuclein oligomers and its role in the pathogenesis of PD is crucial for the development of effective diagnostic and therapeutic strategies.

The results of Zhou and Kurouski’s study showed that the morphology and structure of the oligomers changed with the progression of the aggregation process. The IR spectra of individual oligomers revealed structural rearrangements necessary for oligomers to propagate into fibrils with parallel-β-sheet secondary structure. This study provides insights into the structural organization of α-synuclein oligomers, which is essential to understand its toxicity. Moreover, the findings may contribute to the development of approaches for oligomer detection and pre-symptomatic diagnosis of PD.

Amyloid fibrils are associated with various neurodegenerative diseases and are of significant interest in structural biology. While conventional methods have provided insights into the morphology and core structure of fibrils, characterizing the surface has been challenging.

The formation of amyloid fibrils is a complex process that is associated with various neurodegenerative diseases such as Alzheimer’s, Parkinson’s, and Huntington’s diseases, as well as prion diseases. The accumulation of amyloid fibrils is believed to contribute to the degeneration of neurons and cognitive decline in these diseases. Understanding the structure and formation mechanism of amyloid fibrils is therefore crucial for developing effective treatments for these diseases. Raman spectroscopy has been extensively used to investigate protein aggregation and amyloid fibril formation due to its ability to reveal changes in secondary and tertiary structures at all stages of fibrillation. When combined with atomic force and scanning electron microscopies, 

Raman spectroscopy becomes a powerful approach for investigating the structural organization of amyloid fibril polymorphs, which can provide valuable insights into its formation and potential therapeutic targets.

, Kurouski and colleagues used tip-enhanced Raman spectroscopy (TERS) to probe the surface structure of insulin fibrils (4). The study demonstrated that TERS can provide high-resolution insights into the secondary structure and amino acid residue composition of the fibril surface. The insulin fibril surface was found to be strongly heterogeneous, with clusters exhibiting different protein conformations. More than 30% of the surface was dominated by β-sheet secondary structure, supporting Dobson’s model of amyloid fibrils. The study also revealed the distribution of various amino acids on the fibril surface and specific surface secondary structure elements. Cysteine and aromatic amino acids such as phenylalanine and tyrosine were found to be enriched in β-sheet areas, whereas proline was only found in α-helical and unordered protein clusters. The study also showed that carboxyl, amino, and imino groups were nearly equally distributed over β-sheet and α-helix/unordered regions.

, Kurouski and coauthors explore the applications of Raman spectroscopy in the structural characterization of amyloidogenic proteins, prefibrillar oligomers, and mature fibrils (5). The review summarizes various techniques that have been used in conjunction with Raman spectroscopy to provide a comprehensive understanding of the structure and formation mechanism of amyloid fibrils. The article highlights that Raman spectroscopy is a unique, label-free and nondestructive technique that can reveal the structural changes of amyloid fibrils during the fibrillation process. Amyloid fibrils are protein aggregates that form when proteins misfold and aggregate together in a β-sheet structure.

Plant pathogens are microorganisms that can infect and cause diseases in plants, leading to significant yield losses and reduced crop quality. Maize kernels, which are important sources of food and feed, are particularly susceptible to various pathogens, such as fungi and bacteria. These pathogens can cause symptoms such as discoloration, mold growth, and reduced kernel size, which negatively impact both yield and quality. Early detection and identification of these pathogens are critical for effective disease management and prevention. In this context, nondestructive and noninvasive techniques such as Raman spectroscopy are promising tools for rapid and accurate diagnosis, as demonstrated in the study published in 

In this study, researchers aimed to develop a rapid and nondestructive method for detecting and identifying plant pathogens on maize kernels, which is crucial for improving crop yield. They used a hand-held Raman spectrometer along with chemometric analysis to distinguish between healthy and diseased maize kernels and different diseases with 100% accuracy. Raman spectroscopy is a noninvasive and nondestructive technique that provides information about the chemical structure of a specimen. The sample-agnostic and portable nature of the analysis suggests that it could be retooled for other crops and conducted autonomously. This approach offers advantages over traditional pathogen assaying methods such as polymerase chain reaction (PCR) or enzyme-linked immunosorbent assay (ELISA), which are time-consuming and destructive to the sample. The study demonstrated the feasibility of using Raman spectroscopy for pathogen detection and identification, which could potentially have a significant impact on crop management and food security. The use of handheld Raman spectrometers allows for the implementation of this technique in the field, enabling rapid and accurate diagnosis of plant diseases, and facilitating prompt management decisions that can help protect crops from further damage.

Kurouski’s contributions to the field of molecular spectroscopy have been both significant and varied. His work in the area of Raman spectroscopy has led to the development of new, noninvasive methods for analyzing plant health and has demonstrated the potential of this technique for use in agriculture. Additionally, his work in the area of nano-Raman-nano-IR imaging has shed new insights into the structure of amyloid oligomers and protein aggregates that are linked to neurodegenerative diseases. His work in the area of plasmon-driven catalysis has elucidated the underlying physical causes of unique reactivity and selectivity in bimetallic nanostructures.

Kurouski’s accomplishments have not gone unnoticed, as evidenced by his numerous awards and honors, including the 2023 Emerging Leader in Molecular Spectroscopy Award from 

magazine. His publication record, which includes over 140 papers with more than 4,000 citations, and his extensive record of conference presentations demonstrate the impact of his research on the field of molecular spectroscopy.

Looking to the future, it seems likely that Kurouski will continue to make significant contributions to the field of molecular spectroscopy. His work has already demonstrated the potential of Raman spectroscopy for use in agriculture and for diagnostics of viral particles. As his research continues to progress, it seems likely that his work will continue to open new doors in this exciting and important field.

(1) Kurouski, D.; Postiglione, T.; Deckert-Gaudig, T.; Deckert, V.; Lednev, I. K. Amide I vibrational mode suppression in surface (SERS) and tip (TERS) enhanced Raman spectra of protein specimens. 

 (6), 1665–1673. DOI: 10.1039/C2AN36478F

(2) Kurouski, D.; Dazzi, A.; Zenobi, R.; Centrone, A. Infrared and Raman chemical imaging and spectroscopy at the nanoscale. 

 (11), 3315–3347. DOI: 10.1039/C8CS00916C

(3) Zhou, L.; Kurouski, D. Structural Characterization of Individual α-Synuclein Oligomers Formed at Different Stages of Protein Aggregation by Atomic Force Microscopy-Infrared Spectroscopy. 

 (10), 6806–6810. DOI: 10.1021/acs.analchem.0c00593

(4) Kurouski D.; Deckert-Gaudig T.; Deckert V.; Lednev I.K. Structure and Composition of Insulin Fibril Surfaces Probed by TERS. 

(32), 13323–13329. DOI: 10.1021/ja303263y

(5) Kurouski, D.; Van Duyne, R. P.; Lednev, I. K. Exploring the structure and formation mechanism of amyloid fibrils by Raman spectroscopy: a review. 

 (15), 4967–4980. DOI: 10.1039/C5AN00342C

(6) Farber, C.; Kurouski, D. Detection and Identification of Plant Pathogens on Maize Kernels with a Hand-Held Raman Spectrometer. 

 (5), 3009–3012. DOI: 10.1021/acs.analchem.8b00222

Featured Article

Dmitry Kurouski is this year’s recipient of the 2023 Emerging Leader in Molecular Spectroscopy Award for his work in using Raman spectroscopy for noninvasive, nondestructive analyses of biological materials.

The 2023 Emerging Leader in Molecular Spectroscopy Award

Fourier transform infrared (FT-IR) spectroscopy has attracted great attention in the field of disease diagnostics for many years. Yet, the clinical translation of FT-IR spectroscopy has been rather slow because of several bottlenecks. This work explores the potential of aluminum foil-assisted attenuated total reflectance-FT-IR (ATR-FT-IR) spectroscopy, which is a simple and economical FT-IR sampling technique, to detect acute kidney injury (AKI) induced by gentamicin in a rat model. It was found that partial least squares-discriminant analysis (PLS-DA) could successfully discriminate between the AKI status and the healthy status with the plasma samples of the rats. An in-depth discussion on the advantages of aluminum-foil-assisted ATR-FT-IR spectroscopy in FT-IR-based disease diagnostics is also provided.

Fourier transform infrared (FT-IR) spectroscopy is a rapid, non-invasive, and label-free analytical technology and has attracted great attention in the field of disease diagnostics for many years (1–6). As a vibrational spectroscopic tool, FT-IR spectroscopy has the capability to detect the vibrations of all molecules, such as proteins, nucleic acids, lipids, and carbohydrates in a clinical specimen. Thus, FT-IR spectroscopy can provide a comprehensive omnic picture of the tested sample. Owing to its sensitivity to the compositional and structural changes inside the clinical specimen,
FT-IR-based diagnostics can provide a spectral biomarker for diseases. The spectral biomarker can be a single spectral band or multiple spectral bands demonstrating the disease characteristics, or the whole spectral fingerprint can be used to discriminate the different health status when enabled using chemometric analysis.

To date, FT-IR-based diagnostics has been applied to a variety of clinical samples, including tissues (7–9), plasma and serum (10–16), and body fluids (17–20). Many proof-of-principle studies have clearly demonstrated the potential of FT-IR-based diagnostics for human diseases in clinical translation. Some startup companies aiming at translation to clinical applications were also established (2).

Aluminum-foil-assisted ATR-FT-IR spectroscopy was an FT-IR sampling approach developed by Martin and coworkers in 2016 (21). When implementing this approach, kitchen-grade aluminum foil may be used as the solid substrate for sample deposition. After a simple drying step, the deposited sample is pressed against the ATR crystal for FT-IR measurement. This sampling approach avoids the direct use of the ATR crystal or other expensive substrates for sample deposition during ATR-FT-IR measurement. It could significantly reduce the sampling cost and simplify the sampling procedure in clinical applications. The aluminum-foil-assisted ATR-FT-IR approach has now emerged as an attractive sampling approach for FT-IR-based disease diagnostics (20, 22–25). For example, one demonstration was performed very recently by Nascimento et al. where they used this approach to detect Covid-19 within saliva samples. By combining chemometric analysis with the spectra, they reported reasonable accuracy and sensitivity for Covid-19 diagnostics (20). This work aims to further tackle the potential of the aluminum-foil-assisted ATR-FT-IR approach in disease diagnostics by using this technique to detect acute kidney injury (AKI) status induced by gentamicin in a rat model. We hope that this exploratory work is beneficial for the future development of FT-IR-based disease diagnostics.

 = 3) were purchased from Vital River Lab Animal Technology Co., Ltd (Beijing, China). The rats were housed with free access to food and water under constant temperature, humidity, and lighting (12 h light per day). The animal experiment was carried out strictly according to the ethics guidelines for the care and use of laboratory animals approved by the Animal Ethics Committee of Tianjin Tasly Institute, Tianjin, China. The rats were dosed with gentamicin (160 mg/kg) in saline to establish an AKI rat model. The dose of gentamicin used in this work was referred to as that used in a previous publication (26,27). These rats were injected with gentamicin for three consecutive days; that is, on day one, day two, and day three. The gentamicin sulfate injection solution was obtained from CSPC Pharmaceutical Group Co., Ltd. (Shijiazhuang, China). Sodium chloride (NaCl) was in analytical grade and ordered from a local vendor.

Sample Preparations for ATR-FT-IR Measurements

The whole blood samples from the rats were collected through retro-orbital blood sampling. The samples taken on day one before gentamicin injections were from the healthy rats, and they were used as the control group in the chemometric analysis of plasma samples; the samples taken on day two and day three before gentamicin injections and on day four were from the rats affected by gentamicin (from the AKI rats), and they were used as the AKI group in the chemometric analysis of plasma samples. The whole blood sample was centrifuged at 3000 r/min for 10 min and the supernatant plasma was collected and stored at -80 °C for future ATR-FT-IR investigation. To prepare the plasma sample for aluminum-foil-assisted ATR-FT-IR measurement, a large piece of kitchen-grade aluminum foil was cleaned with alcohol and water and then air-dried. The large piece of aluminum foil was cut into small pieces with a size of 1 x 1 cm. The plasma sample was first thawed under ambient conditions and 10 µL of the sample was pipetted onto the small piece of aluminum foil. The aluminum foil with sample deposit was placed in an oven at 37 °C for 2 hr. The sample formed a dry film on the surface of the aluminum foil. The dry plasma sample film was used for ATR-FT-IR measurement.

Aluminum-Foil-Assisted ATR-FT-IR Measurement

The details of aluminum-foil-assisted ATR-FT-IR measurement are shown in Figure 1 Measurements were made using a Bruker Vertex 70 FT-IR spectrometer (Ettlingen, Germany) equipped with a DLaTGS detector. A Pike Technologies single-reflection ATR sampling accessory (Madison, Wisconsin) was employed. This ATR sampling accessory contained a diamond ATR crystal. As shown in Figure 1, when performing the measurement, the surface of aluminum foil having plasma deposition was pressed against the ATR diamond crystal surface with a manual pressure clamp from Pike Technologies. The high-pressure of the pressing device would ensure a close contact between the sample and the diamond crystal. For the FT-IR measurements, 4 cm

A recent study used aluminum foil-assisted ATR-FT-IR spectroscopy to detect acute kidney injury (AKI) in a rat model using plasma samples. The results 
show how ATR-FT-IR could be used to study more types of clinical samples in the future.

September 2023

Guess Who’s Coming to Inspect R&D?

Halogenated Organic Compounds

The 2023 Emerging Leader in Molecular Spectroscopy Award

Detection of Acute Kidney Injury Induced by Gentamicin in a Rat Model by Aluminum-Foil-Assisted ATR-FT-IR Spectroscopy

Review and Prospect: Applications of Exponential Signals with Machine Learning in Nuclear Magnetic Resonance