In this episode of ‪ChromatographyTalk‬, ‪Organomation‬ General Manager David Oliva sits down with Imad Haidar Ahmad, Scientific Research Director at Amgen leading separations for Discovery Chemistry and Externalization. Imad's career spans Novartis, Merck, and now Amgen, and his research on computer-assisted method development has landed multiple front covers in Analytical Chemistry.We dig into how his group builds retention models from as few as nine lab experiments to map an entire separation landscape — replacing weeks of trial and error with a resolution map you can query and rebuild from. Imad breaks down where this modeling approach struggles (large molecules, SFC, fully autonomous method development), walks through two-dimensional liquid chromatography in plain terms for anyone who's only worked in 1D, and shares the story behind his group's greenness-score mapping work — including where swapping acetonitrile for methanol worked, and where it didn't.We also talk career advice: what a typical day looks like leading a discovery-stage separations team, how undergrad and grad students can bridge the academia-to-industry gap, and what Imad sees as the field's biggest unsolved problem.<h3>Video Transcription</h3>Chromatographic method development is increasingly moving beyond trial and error toward workflows built on modeling, automation, multidimensional separations, and smarter use of data. In a recent interview, Haidar Ahmad discussed how these approaches are changing pharmaceutical analysis, why understanding the fundamentals of chromatography remains essential, and where some of the biggest opportunities in separation science still lie.Ahmad’s route into analytical chemistry was not entirely planned. As an undergraduate, he initially found inorganic and organic chemistry particularly attractive, but a final-year project focused on the analysis of additives in bread introduced him to the possibilities of analytical chemistry. During his PhD, his research moved into polymer analysis and structure–property relationships. His interest in chromatography deepened when he encountered two-dimensional liquid chromatography (2D-LC), particularly its ability to reveal forms of polymer heterogeneity that could not be adequately characterized using a single separation technique. This eventually led to postdoctoral work with Peter Carr, where Ahmad focused on chromatographic separations and the fundamentals of chromatography.His subsequent career in the pharmaceutical industry exposed him to different stages of drug development, from late-stage method development and validation to drug substance characterization, purification, and finally discovery-stage separations. That breadth of experience has shaped his view of chromatography as both a scientific discipline and a practical problem-solving tool. In late-stage development, the objective may be a highly robust method capable of successful validation and transfer between laboratories. In discovery, by contrast, speed becomes critical because teams may be working with thousands of molecules while trying to identify the best candidates to advance.&nbsp;<h4>Discovery-stage chromatography: speed, prioritization, and throughput</h4>For a separations team supporting drug discovery, the working day is shaped by a constant flow of requests from medicinal chemistry and other partner groups. The challenge is not simply to perform the analyses, but to decide which requests are most urgent, remove bottlenecks, communicate with project teams, and continuously improve existing workflows.According to Ahmad, one of the most important questions is whether a task can be done faster or in a more high-throughput way. Discovery laboratories operate under strong time pressure, and efficiency therefore becomes part of the scientific strategy rather than merely an operational concern. As he describes it, the work combines science, prioritization, leadership, and communication, all with the aim of moving the most important projects forward as quickly as possible.<h4>In silico modeling: letting the computer perform the experiments</h4>One of the central themes of Ahmad’s work is in silico chromatographic modeling. In practical terms, the approach begins with a carefully designed set of laboratory experiments—often around nine runs. The resulting data are fed into software that builds retention models describing how analyte retention changes with variables such as mobile-phase composition and temperature.The software can then generate a resolution map representing a much larger separation space than could realistically be tested experimentally. Instead of running dozens or hundreds of conditions by trial and error, the analyst can identify regions where critical peak pairs are predicted to achieve the best separation.For Ahmad, the value of these maps goes beyond simply finding the condition with the highest resolution. Each point on the map represents a chromatographic condition, while the visual output shows where poor and strong separations are expected. A broad region of good resolution is particularly useful because it points toward a more robust operating space rather than a narrowly defined optimum that might be sensitive to small variations in experimental conditions.He therefore prefers to think of a chromatographic model as a map or database, rather than simply an optimization tool. If an impurity later disappears from the process, the corresponding peak can be removed from the model and new conditions selected without repeating the complete experimental study. Conversely, if a new degradation product appears during stability studies, the peak can be added and the existing model used to search for updated separation conditions.<h4>Why trial and error still has a place</h4>Modeling does not mean that conventional trial-and-error method development has disappeared. Ahmad points out that it remains useful in early discovery, particularly for fit-for-purpose methods where speed is more important than achieving a fully optimized separation.The situation changes later in development. A method intended for validation, transfer, or long-term routine use carries much greater risk. Trial and error may identify a condition that appears satisfactory without revealing whether it represents the most robust region of the separation space. If that method later fails during transfer or routine operation, the consequences can be costly.For late-stage methods, the additional investment required to build a model can therefore reduce risk over the much longer lifetime of the analytical procedure.<h4>Models are only as good as the experiments behind them</h4>Chromatographic modeling is not automatic proof against poor method development. Ahmad compares the technology to a GPS: it is highly useful, but only if the analyst understands where they are trying to go.Careful experimental design remains essential. Incorrect dwell-volume or column-volume information, as well as insufficient column re-equilibration, can produce misleading predictions. Importantly, these problems may not be obvious when the experimental runs used to construct the model are compared with their calculated values. They may emerge only when the software begins predicting new conditions within the modeled design space.Modeling is also easier for some separations than others. Ahmad describes reversed-phase LC of small molecules as comparatively straightforward, while large biomolecules are more challenging because their retention can be highly sensitive to small changes in mobile-phase composition and temperature.Other separation modes present additional difficulties. Ahmad notes that his teams have found supercritical fluid chromatography (SFC) particularly challenging to model successfully. Fully autonomous method development remains another unresolved goal: current tools can automate parts of optimization, but analyst input is still required.<h4>Why two dimensions can reveal what one dimension cannot</h4>Ahmad’s early interest in 2D-LC came from polymer characterization. He explains the principle simply: one-dimensional chromatography may answer one question about a sample, while two complementary dimensions can answer two.Two copolymers, for example, may have similar molecular size and therefore coelute in size-exclusion chromatography. A second separation mechanism based on interaction with a stationary phase may distinguish them according to chemical composition. Combining both dimensions provides a more complete description of complex distributions involving molecular weight, composition, sequence, and other forms of heterogeneity.Historically, the complexity of both instrumentation and software limited wider adoption of 2D-LC. Ahmad recalls systems requiring several computers and multiple software packages. That situation has improved substantially, and 2D-LC is now easier to implement across research and pharmaceutical development.Nevertheless, modeling multidimensional separations still presents challenges. While models can be built for individual fractions or dimensions, current software does not easily identify a common optimum across multiple models simultaneously. Much of this comparison still requires manual work.<h4>Bringing sustainability into method development</h4>Another area where Ahmad sees room for change is green analytical chemistry.Traditional pharmaceutical method development has understandably prioritized resolution, sensitivity, robustness, and turnaround time. Sustainability has often been treated as a secondary consideration, particularly at the analytical scale, where solvent use appears small compared with preparative chromatography or manufacturing.That mindset is beginning to change. Ahmad argues that greenness metrics should increasingly be incorporated directly into method-development software. If analysts could immediately see how changes in flow rate, gradient conditions, solvent choice, or other parameters affect the environmental profile of a method, sustainability could become part of routine optimization rather than an assessment performed after the method has already been developed.The objective, however, is not to pursue the greenest possible method regardless of analytical performance. Ahmad emphasizes the need to develop methods that are as green as possible while remaining fit for purpose. Modeling can potentially help balance these competing requirements by identifying conditions that preserve separation performance while allowing greener solvents or alternative chromatographic conditions to be introduced.<h4>Advice for young chromatographers: do not treat HPLC as a black box</h4>For students learning chromatography, Ahmad’s central recommendation is straightforward: do not treat the HPLC system as a black box.Rather than collecting chromatograms by making random changes, he encourages analysts to build a mental model of the separation. When temperature, gradient, or another parameter is changed, they should ask why retention or selectivity changed and use each experiment to improve their understanding of the system.He also recommends making use of educational resources on chromatographic fundamentals and method development and, importantly, not being afraid to experiment with instrument conditions. Modern systems are robust, but the analyst still needs to understand the underlying separation science in order to use them effectively.The same proactive attitude applies to career development. Ahmad strongly encourages students to seek industry internships and make connections beyond their own institutions. Conferences and poster sessions can provide natural opportunities to meet scientists from industry, discuss research, and ask about internship opportunities. Based on his own experience working with undergraduate and graduate interns, these collaborations can benefit both students and research teams and may strongly influence later academic or career decisions.<h4>What still needs to be solved?</h4>Asked about the biggest unresolved challenges in separation science, Ahmad does not begin with technology. Instead, he points to a shortage of well-trained analytical chemists with a strong understanding of chromatographic fundamentals.Alongside education, he identifies several technical opportunities. One is truly autonomous method development, where an instrument and software could optimize a separation without continuous analyst input. Another is the ability to predict chromatographic selectivity directly from molecular structure.Such capability could be especially valuable in high-throughput discovery environments. If a laboratory could predict which stationary phase and conditions were most likely to separate a particular set of compounds or isomers before entering the laboratory, method development could become considerably faster and more efficient.Taken together, Ahmad’s perspective points toward a future in which chromatography becomes increasingly model-driven, automated, multidimensional, and sustainability-aware. But the technology does not eliminate the need for chromatographic knowledge. On the contrary, as analytical tools become more powerful, understanding the fundamentals may become even more important—the software can explore the separation space, but the scientist still needs to know what question to ask and how to interpret the answer.<blockquote>This text has been automatically transcribed from a video presentation using AI technology. It may contain inaccuracies and is not guaranteed to be 100% correct.</blockquote><blockquote><h4>Concentrating on Chromatography Podcast</h4>Dive into the frontiers of chromatography, mass spectrometry, and sample preparation with host David Oliva. Each episode features candid conversations with leading researchers, industry innovators, and passionate scientists who are shaping the future of analytical chemistry. From decoding PFAS detection challenges to exploring the latest in AI-assisted liquid chromatography, this show uncovers practical workflows, sustainability breakthroughs, and the real-world impact of separation science. Whether you’re a chromatographer, lab professional, or researcher you'll discover inspiring content!You can find Concentrating on Chromatography Podcast in podcast apps:<ul><li><a target="_blank" rel="noopener noreferrer" href="https://open.spotify.com/show/1wZg67rCjoGju4yhqxI3tL">Spotify</a></li><li><a target="_blank" rel="noopener noreferrer" href="https://podcasts.apple.com/tz/podcast/concentrating-on-chromatography/id1788429185">Apple podcast</a></li><li><a target="_blank" rel="noopener noreferrer" href="https://podscan.fm/podcasts/concentrating-on-chromatography">podscan</a></li></ul>and on <a target="_blank" rel="noopener noreferrer" href="https://www.youtube.com/@ChromatographyTalk/videos">YouTube channel</a></blockquote>

 In Silico Modeling, 2D-LC & Green Chromatography: Imad Ahmad on the Future of Method Development

Researchers from CATRIN at Palacký University, together with colleagues from VSB – Technical University of Ostrava and Charles University, have developed a new graphene ink for producing inexpensive and sensitive printed sensors. Using single-atom engineering, they incorporated copper atoms into the material, enabling highly sensitive detection of dopamine – a neurotransmitter responsible for transmitting signals between nerve cells. The approach, <a target="_blank" rel="noopener noreferrer" href="https://advanced.onlinelibrary.wiley.com/doi/10.1002/advs.76796">presented in the journal Advanced Science</a>, has strong potential for use in medical diagnostics.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/CATRIN_Atom_po_atomu_Vedci_ukazali_novy_smer_v_lekarske_diagnostice_8a02ad6a66.webp" alt="CATRIN: Atom by atom. Scientists reveal a new direction in medical diagnostics" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_CATRIN_Atom_po_atomu_Vedci_ukazali_novy_smer_v_lekarske_diagnostice_8a02ad6a66.webp 117w," sizes="100vw" width="1920" height="2560">Single-atom engineering makes it possible to control the chemical reactivity of materials at the level of individual atoms. Its broader application in medical diagnostics has so far been limited by a lack of atomically engineered materials and printable inks based on them. Researchers have now developed a new class of single-atom-doped graphene materials as well as an ink for producing sensitive printed sensors. Copper proved particularly effective for dopamine detection, which is important for biomedical research and the development of advanced diagnostic technologies for diseases including Alzheimer’s disease.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/CATRIN_Atom_po_atomu_Vedci_ukazali_novy_smer_v_lekarske_diagnostice_2_97e419f039.webp" alt="CATRIN: Atom by atom. Scientists reveal a new direction in medical diagnostics" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_CATRIN_Atom_po_atomu_Vedci_ukazali_novy_smer_v_lekarske_diagnostice_2_97e419f039.webp 117w," sizes="100vw" width="1920" height="2560">“The NGA-Cu ink we developed enables the production of fully inkjet-printed, sustainable paper-based electrodes at very low cost. Each sensor requires only 1.3 micrograms of active ink, costs approximately one Czech koruna and provided a stable response for at least three months. The ink is also fully compatible with commonly available materials inkjet printers. This creates significant potential for producing affordable, digitally designed sensors whose function can be tailored atom by atom,” said&nbsp;the corresponding author of the <a target="_blank" rel="noopener noreferrer" href="https://advanced.onlinelibrary.wiley.com/doi/10.1002/advs.76796">paper</a> Michal Otyepka.The basis for this new generation of single-atom inks was nitrogen-doped graphene acid (NGA), which CATRIN researchers developed several years ago. They have now progressively enriched it with different individual metal atoms, including copper, iron and manganese.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/CATRIN_Atom_po_atomu_Vedci_ukazali_novy_smer_v_lekarske_diagnostice_3_c15d831792.webp" alt="CATRIN: Atom by atom. Scientists reveal a new direction in medical diagnostics" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_CATRIN_Atom_po_atomu_Vedci_ukazali_novy_smer_v_lekarske_diagnostice_3_c15d831792.webp 117w," sizes="100vw" width="1920" height="2560">“We found that the electrochemical response depends fundamentally on the type of atom used. While copper atoms significantly enhance the dopamine signal, other metals suppress it. What matters, therefore, is not only the presence of isolated metal atoms but also the specific metal involved. This is a very important finding for the further development of biosensors,” explained first author Martin-Alex Nalepa.The published results introduce a new class of sensing materials with considerable potential for medical diagnostics. The researchers present a broadly applicable platform for developing graphene inks containing individual metal atoms and open the way towards scalable, reproducible and material-efficient production of advanced electrochemical sensors.&nbsp;“We are only at the beginning and are fascinated by the new possibilities opening up before us. We can see that by changing the type of atom, we can control the sensitivity and selectivity of the sensor. In addition to dopamine, we can also determine immunoglobulins very precisely – antibodies whose levels and types may serve as important indicators of autoimmune or infectious diseases,” emphasised Radek Zbořil, a co-author of the paper.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/CATRIN_Atom_po_atomu_Vedci_ukazali_novy_smer_v_lekarske_diagnostice_4_273cd760a5.webp" alt="CATRIN: Atom by atom. Scientists reveal a new direction in medical diagnostics" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_CATRIN_Atom_po_atomu_Vedci_ukazali_novy_smer_v_lekarske_diagnostice_4_273cd760a5.webp 117w," sizes="100vw" width="1920" height="2560">Electrochemical biosensors can find applications not only in medicine but also in food quality control, drinking-water monitoring and environmental pollution monitoring. Their key components are functionalised electrodes, and graphene-based materials have proved particularly suitable for their production. A key factor in the success of the Olomouc researchers was the targeted preparation of graphene ink with the required properties.The research was supported by the TECHSCALE project under the Johannes Amos Comenius Programme.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/CATRIN_Atom_po_atomu_Vedci_ukazali_novy_smer_v_lekarske_diagnostice_5_b1778f77f2.jpg" alt="CATRIN: Atom by atom. Scientists reveal a new direction in medical diagnostics: Project TECHSCALE (No. CZ.02.01.01/00/22_008/0004587) is financed by the MEYS OP JAC Excellent research programme, supported by ERDF/ESF." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_CATRIN_Atom_po_atomu_Vedci_ukazali_novy_smer_v_lekarske_diagnostice_5_b1778f77f2.jpg 245w," sizes="100vw" width="620" height="87"><blockquote><h4>Article</h4><h4><a target="_blank" rel="noopener noreferrer" href="https://advanced.onlinelibrary.wiley.com/doi/10.1002/advs.76796">Single-Atom-Enhanced Fully Inkjet-Printed Electrochemical Sensor for Dopamine Detection</a></h4>Martin-Alex Nalepa, David Panáček, Vítězslav Hrubý, Matěj Jendřišák, Rostislav Langer, Michal Langer, Petr Jakubec, Ivan Dědek, Vojtěch Kupka, Michal Mazur, Radek Zbořil, Michal OtyepkaAdv. Sci., 2026, e76796<a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1002/advs.76796">https://doi.org/10.1002/advs.76796</a><h6>licenced under <a target="_blank" rel="noopener noreferrer" href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a></h6></blockquote><h4>Abstract</h4>Single-atom (SA) engineering offers atomic-level control over interfacial reactivity, yet the lack of printable SA-based inks hinders its practical translation into electrochemical sensing. Here, a fully water-based inkjet-printable ink is introduced based on nitrogen-doped graphene acid (NGA) hosting atomically dispersed Cu centers (NGA-Cu-ink). The ink enables digitally controlled, spatially defined deposition and fabrication of low-cost ($0.04 per sensor), fully inkjet-printed sustainable electrodes on paper. A comparison of NGA functionalized with different SA dopants (Cu, Mn, Fe, Ce) identifies a strong dopant-dependent electrochemical response, with Cu uniquely enhancing the analyte signal while other dopants suppress it, demonstrating that SA identity is a decisive design parameter in printed sensing interfaces profiling sensitivity and selectivity. The functional role of the NGA support is to provide dense anchoring sites (nitrogen and carboxylate groups) that stabilize atomically dispersed metal centers and create adsorption- and electron-transfer–active microenvironments. The NGA-Cu-ink yields enhanced dopamine oxidation, enabling quantitative detection on fully printed devices (limit of detection 9.7 µM; linear range 50–400 µM) and printed-on-electrode platforms (10.6 µM), while maintaining &lt;10% signal variation over 11 weeks. The approach establishes a general route to single-atom graphene-based inks for scalable, reproducible, and low-material-consumption manufacturing of advanced electrochemical sensors.

Atom by atom. Scientists reveal a new direction in medical diagnostics

<div><div>Accurately predicting NMR chemical shifts remains difficult for protons that can exchange with their environment in solution. These protons are covalently bound to electronegative atoms in hydroxyl (-OH), amine (-NH), and thiol (-SH) group. Their NMR signals are highly sensitive to hydrogen bonding, interactions with the solvent, and the continuous motion of molecules. Conventional DFT calculations typically treat the solvent in a simplified manner, often overlooking important interactions between dissolved molecules and their surroundings. A new computational approach developed by scientists led by <a target="_blank" rel="noopener noreferrer" href="https://nmr.group.uochb.cz/en">Martin Dračínský</a> from IOCB Prague addresses this problem by combining machine-learning (ML) molecular dynamics (MD) with ShiftML3, a machine-learning model for rapid prediction of NMR shielding.</div></div><div>The method first uses ML-based molecular dynamics to generate realistic ensemble of molecular structures in solution, capturing the constantly changing hydrogen-bonding patterns. ShiftML3 then predicts the chemical shifts for each configuration within fractions of a second. Although the model was originally developed for molecular solids, it also performs remarkably well in solutions. In molecular crystals, molecules are surrounded by close neighbors and experience a wide variety of intermolecular contacts, many of which closely resemble the interactions found in liquids.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/IOCB_Prague_Accurate_NMR_chemical_shifts_through_machine_learned_dynamics_2_a5e7404cff.webp" alt="IOCB Prague: Accurate NMR chemical shifts through machine-learned dynamics: A new computational approach developed by scientists led by Martin Dračínský from IOCB Prague addresses addresses often overlooked issues with simplified conventional DFT calculations. Nat. Commun. 2026, 17, 8842." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_IOCB_Prague_Accurate_NMR_chemical_shifts_through_machine_learned_dynamics_2_a5e7404cff.webp 245w," sizes="100vw" width="1620" height="911">The researchers validated the approach on chemically diverse systems, including water in organic solvents, alcohols, hydrogen-bonded nucleobases, glucose anomers, and alkylated acetamides. In all cases, the combination of ML-based molecular dynamics and ShiftML3 reproduced experimental chemical shifts with high accuracy, especially for exchangeable protons in OH and NH groups, whose signals are particularly sensitive to their local environment.The results show that combining ML-based molecular dynamics with rapid NMR chemical-shift prediction can substantially improve the accuracy of calculations for flexible and hydrogen-bonded molecules in solutions. The main advantage of the framework is that it can evaluate hundreds or thousands of solvent configurations without requiring an expensive quantum-mechanical calculation for each one. This opens the way to faster and more reliable prediction of NMR spectra, with potential applications in signal assignment, molecular structure determination and structural validation.<blockquote><h4>The original article</h4><h4><a target="_blank" rel="noopener noreferrer" href="https://www.nature.com/articles/s41467-026-75743-w">Quantitative Prediction of Exchangeable Proton Chemical Shifts</a></h4>Ondřej Socha, Jana Pavlišová, Debashree Manna &amp; Martin DračínskýNat. Commun., 2026, 17, 8842<a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1038/s41467-026-75743-w">https://doi.org/10.1038/s41467-026-75743-w</a>&nbsp;<h6>licenced under <a target="_blank" rel="noopener noreferrer" href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a></h6></blockquote><h4>Abstract</h4>Accurately predicting NMR chemical shifts of exchangeable protons in solution remains challenging because of the combined influence of solute–solvent interactions and molecular dynamics. We introduce a framework that integrates machine-learning molecular dynamics (ML-MD) with the ShiftML3 machine-learning shielding model for rapid and accurate prediction of NMR spectra in solvated molecules. Although originally developed for solids, ShiftML3 effectively captures intermolecular contributions to shielding in solution. We validate the method across a range of chemically diverse systems, including water in organic solvents, solvated alcohols, hydrogen-bonded nucleobases, glucose anomers, and alkylated acetamides. The ML-MD + ShiftML3 framework reproduces experimentally observed chemical shifts of exchangeable protons with near-quantitative accuracy, resolving subtle hydrogen-bonding and conformational effects that implicit-solvent DFT fails to capture. These results establish ML-MD + ShiftML3 as a transferable and computationally efficient way of incorporating solvation and dynamics into NMR spectroscopy, enabling realistic chemical shift predictions for flexible, hydrogen-bonded, and complex molecular systems.</div>

Accurate NMR chemical shifts through machine-learned dynamics

Article

Scientists

Interview

Science and research

Video

The Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences (IOCB Prague) is a leading scientific institution in the Czech Republic, recognized internationally. Its primary mission is basic research in the fields of chemical biology and medicinal chemistry, organic and material oriented chemistry, chemistry of natural compounds, biochemistry and molecular biology, physical chemistry, theoretical chemistry, and analytical chemistry. 

Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences

The Czech Advanced Technology and Research Institute (CATRIN) at Palacký University is a cutting-edge scientific hub dedicated to advancing research in the fields of nanotechnology, biotechnology, and biomedicine. At its core, CATRIN boasts outstanding scientific teams, featuring international researchers. We emphasize interdisciplinarity, foster global collaborations, and work to translate our research findings into practical applications.

CATRIN

Organomation, founded in 1959, designs and manufactures high-quality nitrogen evaporators and extraction systems. Known for innovation and durability, their lab instruments are used globally for efficient sample preparation with strong customer support.

Organomation

Agilent Technologies

Technology Networks

Bruker

Thermo Fisher Scientific

SelectScience

C&EN

Waters Corporation

Join Dr. Jens Lättig from Tecan and Dr. Cassandra Rusher, European Technical Support Specialist at Eprep, as they explain how the Resolvex® Prep simplifies chromatography and mass spectrometry sample preparation. They will also demonstrate how Resolvex® Prep automates the manual preparation of samples and standards, ensuring consistent performance while minimizing the need for re-validation.
Key learning objectives
<ul>
<li>Learn how the Resolvex® Prep reduces setup time to as little as 5 to 15 minutes, allowing scientists to focus on other critical tasks, while the instrument handles the rest autonomously.</li>
<li>Understand how analytical syringes and specialized tools ensure consistent and reliable results, minimizing the risk of human error in your lab&#39;s processes</li>
<li>Gain insights into achieving reliable, repeatable results across various sample types and workflows</li>
<li>Learn about the versatile capabilities of Resolvex® Prep, including its built-in wash station, RFID deck scan, and seamless sample transfer into analytical instruments, tailored to meet the unique demands of your research</li>
</ul>
Who should attend?
Laboratory scientists and managers from analytical laboratories in: pharma, biopharma, biotech, the food industry, the environmental sector, agriculture, drug screening, proteomics, and metabolomics
Certificate of attendance
All webinar participants can request a certificate of attendance, including a learning outcomes summary, for continuing education purposes.
<blockquote>
Presenter: Jens Lattig, PhD (Sales Development Manager Proteomics &amp; MS Sample Prep, Tecan)
</blockquote>
<blockquote>
Dr. Jens Lättig is a Sales Development Manager Proteomics &amp; MS Sample Preparation at Tecan. He has a PhD in biochemistry, and has worked in drug research projects in Germany and France. At Tecan, he is responsible for the Resolvex™ instruments and consumables portfolio in Europe.
</blockquote>
<blockquote>
Presenter: Cassandra Rusher, PhD (European Technical Support Specialist, Eprep)
</blockquote>
<blockquote>
Dr. Cassandra Rusher is a technical support specialist for the Resolvex Prep. at Eprep. She has a PhD in chemistry and a background specializing in chromatography including sample preparation. Her previous roles have included technical support and product management in the analytical chromatography sector. Her focus now is on supporting the automation of sample preparation methods across a range of industries that are utilizing analytical chromatography techniques.
</blockquote>
<blockquote>
Moderator: Carrie Haslam (Associate Editor, SelectScience) 
</blockquote>

SelectScience: Streamline your sample preparation with Resolvex® prep

Streamline your sample preparation with Resolvex® prep

Specialists from Eprep will explain how the Resolvex® Prep simplifies chromatography and mass spectrometry sample preparation.

Sample preparation with Resolvex® prep

Don’t want the complexity of a valve system for your ICP?
Come along to this webinar where you can find out how StepAhead can help you get analysis done quicker and save money!
<blockquote>
Presenter: Matthew Gregory (Applications Specialist, TEA, Thermo Fisher Scientific)
</blockquote>
<blockquote>
After graduating from the University of Surrey with an MChem in Chemistry, Matthew has gained 20 years’ experience of trace elemental analysis in industry, working in environmental and precious metal research laboratories. In 2018, Matthew joined Thermo Fisher Scientific as an Applications Specialist for the Trace Elemental Analysis product range in the UK and Ireland.
</blockquote>
<blockquote>
Presenter: David Fishwick (Applications Specialist, TEA, Thermo Fisher Scientific)
</blockquote>
<blockquote>
David joined Thermo in 2022 as an Applications Specialist for the Trace Elemental Analysis product range in the UK and Ireland. Prior to joining Thermo, David has gained experience of trace elemental analysis and chromatography in industry, working in GMP, GLP and UKAS accrediated R&amp;D and pharmaceutical laboratories. David holds a BSc in Chemistry from Bangor University. 
</blockquote>

Thermo Scientific: Increasing Lab Productivity with Thermo Scientific iSC-65 with StepAhead for ICP

Increasing Lab Productivity with Thermo Scientific iSC-65 with StepAhead for ICP

Find out how StepAhead can help you get analysis done quicker and save money!

Increasing Lab Productivity with Thermo Scientific iSC-65

Mass spectrometry (MS)-based omics technologies have revolutionized our understanding of molecular changes in organisms and are crucial for studying metabolism and related diseases through lipidomics and metabolomics.
Despite significant advances, there is still a need for robust analytical methodologies in data acquisition, data processing and annotation.
This webinar will demonstrate how LC-Zeno SWATH DIA outperforms conventional DDA in annotating metabolites and lipids in the model organism Gammarus fossarum. Additionally, the presentation will showcase the effectiveness of electron activated dissociation (EAD) in characterizing lipid species and elucidating metabolite isomers. Finally, the webinar will illustrate how EAD and high-resolution targeted approaches improve structural elucidation and molecular network construction.
Attend this webinar to:
<ul>
<li>Learn about the benefits of LC-Zeno SWATH DIA over conventional DDA methods for metabolite and lipid annotation
</li>
<li>Explore the implementation of EAD for enhanced lipid species characterization and metabolite isomer elucidation
</li>
<li>Understand how EAD improves structural elucidation and molecular network construction
</li>
</ul>
<blockquote>
Presenter: Dr. Valentina Calabrese (Postdoctoral Researcher at Institute of Analytical Sciences)
</blockquote>
<blockquote>
Valentina Calabrese received her Ph.D. in Analytical and Bioanalytical Sciences at University of Palermo, Italy and is currently a postdoctoral researcher at the Institute of Analytical Sciences in Lyon, France. During her career, she specialized in high resolution, ultra-high resolution, and ion mobility mass spectrometry for application on fundamental topics and -omics research, such as metabolomics and lipidomics. Her research activity focuses on new method development and unknown compound annotation through high-resolution mass spectrometry and molecular networking in biological complex samples. She is currently involved in the study of sentinel freshwater organisms, as Gammarus fossarum and works on DDA and SWATH DIA methods with CID or EAD fragmentation strategies along with molecular networking construction for improving structural characterization of small molecules.
</blockquote>

Technology Networks: Enhancing MS-Based Omics Analysis in a Model Organism

Enhancing MS-Based Omics Analysis in a Model Organism

How LC-Zeno SWATH DIA outperforms conventional DDA in annotating metabolites and lipids in the model organism Gammarus fossarum.

Learn how Light Scattering can benefit your drug development!
A critical step in the development process for an antibody drug conjugate (ADC) is establishing scientifically sound analytical methods that measure key product quality attributes to support pre-clinical activities and downstream clinical release and stability testing. By leveraging key technologies and platform analytical methods, drug developers can expedite an early-phase biologics’ path to IND by removing analytical method development from the critical path.
Join us on an exploration of the analytical characterization required to confidently assess the ID, safety and efficacy of an antibody drug conjugate (ADC). We will start with a practitioners view on the requisite analytics and then shift to several case studies where multiple techniques, from mass spectrometry to light scattering, were used to interrogate these complex protein conjugates.
This webinar promises a comprehensive look at the analytical processes and technologies needed to successfully advance ADC development.
Key learning topics:
<ul>
<li>How to assess Identification, safety and efficacy of ADCs
</li>
<li>The requirements for characterisation are for ADCs
</li>
<li>How multiple techniques (such as mass spectrometry and light scattering) can be used together to understand complex protein conjugates.
</li>
</ul>
 Who should attend?
<ul>
<li>Quality Control and Drug Development Analytical Scientists, Lab Managers and Scientific Directors who are working with ADC characterisation or protein therapeutics in Pharma</li>
</ul>
<blockquote>
Presenter: Eric Miller (Abzena)
</blockquote>
<blockquote>
Dr. Eric Miller is an accomplished professional with a strong background in analytical chemistry. He has made significant contributions to the biotech industry, particularly through his work on the LabZient™ Analytical Platform.
</blockquote>
<blockquote>
Eric began his journey as a Scientist at ClinMet. He has worked for Agilent Technologies and Pacira Pharmaceuticals before joining Abzena as Senior Director, Scientific Project Leaders, Analytical.
</blockquote>
<blockquote>
His expertise lies in addressing the unique needs of biopharmaceuticals.
</blockquote>
<blockquote>
Presenter: Colette Quinn, Ph.D. (Sr. Business Development Manager, Waters Corporation)
</blockquote>
<blockquote>
Colette Quinn is a Sr. business development manager in the biopharmaceutical group at Waters Corporation. Her focus is around biophysical solutions and how to integrate biophysical and biochemical approaches to enable a “totality of evidence” based approach to problems.
</blockquote>

Waters Corporation: Learning Advanced Analytical Technologies to Expedite the development of Antibody Drug Conjugates

Learning Advanced Analytical Technologies to Expedite the development of Antibody Drug Conjugates

Learn how Light Scattering can benefit your drug development.

Analytical Technologies for Antibody Drug Conjugates

Multiomic and multimodal spatial data from one tissue sample provides actionable information for disease related insights.
Leverage mass spectrometry in the post-genomic era to move beyond the biological determinants of DNA and RNA.Contextualize biological information with proteins and downstream molecules using an innovative benchtop system optimized for ease-of-use.
During this webinar, you will learn:
<ul>
<li>The multiomics capabilities of MALDI Imaging
</li>
<li>The benefits of spatial biology for disease based research
</li>
<li>Ease-of-use of neofleX, a benchtop mass spectrometer for spatial biology
</li>
</ul>
Who should attend:
<ul>
<li>Translational researchers who want advanced spatial biology tools with ease-of-use workflows
</li>
<li>Researchers focused on maximizing spatial multiomics capabilites
</li>
<li>Anyone interested in benchtop mass spectrometers with no compromise on quality register here
</li>
</ul>
<blockquote>
Presenter: Mengzhe Zhang, Ph.D. Candidate, Bernd Bodenmiller Lab, University of Zurich, Zurich, Switzerland
</blockquote>
<blockquote>
Presenter: Janina Oetjen, Ph.D., Imaging Applications Scientist, Bruker Daltonics, Bremen, Germany
</blockquote>
<blockquote>
Presenter: Kate Stumpo, Ph.D., Senior Market Manager, Bruker Scientific, Billerica, MA, USA
</blockquote>

Bruker:  LabCast: Spatial profiling to transform molecular pathway awareness using neofleX

 LabCast: Spatial profiling to transform molecular pathway awareness using neofleX

The multiomics capabilities of MALDI Imaging.

 LabCast: Spatial profiling to transform molecular pathway

Elemental impurities are trace metals or elements that can be present in pharmaceuticals, impacting product safety and efficacy.
USP General Chapter &lt;232&gt; provides guidelines for controlling elemental impurities in pharmaceuticals, ensuring they meet acceptable levels for human consumption. Compliance with USP &lt;232&gt; is crucial for regulatory approval and maintaining product quality and safety.
Register to attend this Webinar and learn:
<ul>
<li>Elemental impurities as per USP 232/USP 233 and ICHQ3D
</li>
<li>Dive into the innovation that powers USP-232 guidelines
</li>
<li>Agilent&#39;s MH software with Agilent&#39;s complete workflow solutions
</li>
<li>Basic maintenance and early maintenance feedback of ICP-MS
</li>
</ul>
<blockquote>
Presenter: Dr. Kuldeep Sharma (Sales Development Manager - Pharma, Agilent Technologies)
</blockquote>
<blockquote>
Kuldeep Sharma has over 19 years of experience in area/s of Bioanalytical research, Drug metabolism &amp; pharmacokinetics and Pharma regulatory compliance. He has accomplished PhD in Biotechnology. His professional journey covers over 12 years in Analytical research (associated with R&amp;D’s of Zydus Cadila, Lambda, Pliva and Jubilant Biosys) and last 7 years in analytical instruments sales, marketing &amp; business development. With over 21 research articles published in international Journals, He presents convention of continues learning.
</blockquote>
<blockquote>
Presenter: Mr. Radhey Shyam (Application Specialist - Spectroscopy, Agilent Technologies)
</blockquote>
<blockquote>
Radhey Shyam is an Application Scientist responsible for Elemental Spectroscopy Solutions at Agilent Technologies at Centre of Excellence (COE) Lab, Manesar. He has been assisting in the development of new methods and applications, as well as providing training and educational activities for customers across various sectors on spectroscopy solutions and technologies for the past 10+ years. He has authored several publications in international journals. In addition, he has also contributed to global application and solution notes from Agilent, with a focus on spectroscopy Market.&quot;
</blockquote>
<blockquote>
Presenter: Mr. Ankush Sharma (Regional Marketing Program Manager- APAC (Pharma &amp; Biopharma), Agilent Technologies)
</blockquote>
<blockquote>
Ankush Sharma is a seasoned professional with over 12 years of extensive experience in sales and marketing across the pharmaceutical and biopharmaceutical sectors. His professional journey commenced with a strong educational foundation, earning a Master&#39;s degree in Biotechnology. Building upon this knowledge, he furthered his academic pursuits by obtaining a Master&#39;s in Business Administration with a specialization in Sales and Marketing, demonstrating his commitment to blending scientific understanding with strategic business acumen. For the past five years, he has been an integral part of Agilent, serving as the Regional Marketing Program Manager for the India and now Asia-Pacific (APAC) region for Pharma and Biopharma Markets.
</blockquote>

Agilent Technologies: Demystifying USP & ICHQ3D Guidelines for Elemental Impurities

Demystifying USP & ICHQ3D Guidelines for Elemental Impurities

Elemental impurities as per USP 232/USP 233 and ICHQ3D.

Demystifying USP & ICHQ3D Guidelines for Elemental Impuritie

X-ray emission spectroscopy (XES) has wide ranging element-selective chemical sensitivity to characterize valence, spin-state, ligand bonds, and more. New developments in laboratory XES instrumentation enable routine sample testing. In conjunction with laboratory X-ray absorption spectroscopy (XAS), the laboratory XES systems are finding wide ranging applications in environmental science, energy storage, and more.
In this session, we will highlight laboratory XES capabilities in two energy regimes: hard X-ray (4.5-20 keV) and tender X-ray (2-5 keV). Across these regimes, element-selective capabilities enable analysis of 3rd row transition metals, sulfur, phosphorus, and more. Join to learn more about the wide ranging capabilities and applications of X-ray emission spectroscopy.
Key Learning Objectives:
<ul>
<li>Introduction to X-ray Emission Spectroscopy and its unique capabilities for materials characterization.</li>
<li>Detailed look into example applications of laboratory XES.</li>
<li>Overview of new lab-scale XES instrumentation.</li>
<li>Understanding the process of conducting a laboratory XES measurement, including a real-time measurement demonstration.</li>
</ul>
Who Should Attend:
<ul>
<li>Research Scientists from Universities or Industries that routinely perform materials characterization.</li>
<li>Materials Characterization Lab Managers and Users interested in understanding new techniques.</li>
<li>Those interested in element-specific, non-destructive material analysis.</li>
</ul>
<blockquote>
Presenter: Dr. William Holden (CTO and Co-founder, easyXAFS)
</blockquote>
<blockquote>
Presenter: Dr. Zachary Lebens-Higgins (Testing and R&amp;D Manager, easyXAFS)
</blockquote>
<blockquote>
Presenter: Dr. Paul Aronstein (Applications Scientist, easyXAFS)
</blockquote>
<blockquote>
Presenter: Melissa O&#39;Meara (Forensic Science Consultant, C&amp;EN Media Group)
</blockquote>

C&EN: Materials Characterization with Lab X-ray Emission Spectroscopy (XES)

Materials Characterization with Lab X-ray Emission Spectroscopy (XES)

We will highlight laboratory XES capabilities in two energy regimes: hard X-ray (4.5-20 keV) and tender X-ray (2-5 keV).

Lab X-ray Emission Spectroscopy (XES)

<h4>Rebroadcast of the Live from the Lab: Solutions for Multi-Omics Research from June 13, 2024</h4>
Native nano-DESI mass spectrometry imaging of proteins up to 230 kDa: Advances in proteoform discovery and identification
In this presentation, Prof. Cooper discusses her recent work in developing native ambient mass spectrometry (NAMs) for structural analysis and spatial analysis of proteins.
In this session, you will hear how to
<ul>
<li>identify intact protein assemblies and protein-ligand complexes directly from tissue sections using Native ambient mass spectrometry (NAMs) </li>
<li>understand the structure and function of proteins and their role in complex biological systems </li>
<li>overcome challenges in NAM, including complex mass spectra and low abundance signals Can&#39;t attend the webinar broadcast? No problem! Register anyway and you will automatically receive the link to the recording.</li>
</ul>
<blockquote>
Presenter: Prof. Helen Cooper (University of Birmingham)
</blockquote>

ThermoFisher Scientific: Advances in proteoform discovery and identification

Advances in proteoform discovery and identification

Native nano-DESI mass spectrometry imaging of proteins up to 230 kDa

Are you tired of dealing with inconsistent LC results? Are you looking to extend the life of your LC columns and improve lab efficiency?
Our upcoming webinar, LC Columns Tips &amp; Tricks, is designed to help you get the most out of your LC columns.
Our expert will share invaluable insights on:
<ul>
<li>Understanding LC column chemistry to optimize separations
</li>
<li>Proper handling of new LC columns for maximum lifespan
</li>
<li>Proven techniques to extend column life and reduce downtime
</li>
<li>Effective column maintenance and troubleshooting strategies
</li>
</ul>
This live webinar is an excellent opportunity to deepen your knowledge, improve your lab efficiency, and reduce operational costs. Whether you&#39;re a seasoned pro or just getting started, you&#39;ll walk away with practical knowledge to elevate your column performance and lifetime. Adham Ahmed will be presenting and answering your questions live.
Who Should Attend?
<ul>
<li>Laboratory Analysts and Scientists who are involved in small molecule pharmaceutical analysis
</li>
<li>Chromatographers seeking to optimize LC column performance
</li>
<li>Quality control professionals aiming to improve data reliability and reproducibility
</li>
<li>Research and development scientists working on method development and validation
</li>
<li>Lab Managers: Leaders looking to improve operational efficiency and extend the lifespan of lab equipment.
</li>
<li>Anyone involved in LC column selection, maintenance, and troubleshooting
</li>
</ul>
<blockquote>
Presenter: Adham Ahmed (Global Product Manager, Thermo Fisher Scientific)
</blockquote>
<blockquote>
Adham Ahmed has 15+ years of experience in particle development and functionality for chromatographic application. Presently, he is the Global Product Manager of the Hypersil BDS and ODS and other columns within the Thermo Fisher Scientific Portfolio. His experience includes working in R&amp;D, application specialist and Product management, with a focus on understanding customer’s challenges and laboratory needs.
</blockquote>

Thermo Scientific: LC Columns Tips & Tricks

LC Columns Tips & Tricks

Our upcoming webinar, LC Columns Tips & Tricks, is designed to help you get the most out of your LC columns.

Join this exclusive webinar to discover advanced strategies for enhancing the quality of lentiviral (LV) vectors in cell therapy manufacturing.Quality defects in LV vectors can significantly affect the efficacy and safety of final cell therapies. Despite their critical importance, there has been minimal focus on controlling and monitoring the quality of LV vectors used in cell therapy manufacture. Of particular concern is the risk of ‘breakthrough expression’ of the transgene, leading to CAR expression in producer cells and on the surface of the LV particle.&nbsp;&nbsp;In this webinar, Lentitek will demonstrate how its promoter system is designed to significantly reduce breakthrough expression of the transgene in producer cells, maximizing the functional LV titer during anti-CD19 CAR vector production. Additionally, the webinar will showcase the Leprechaun platform from Unchained Labs, which promises precise identification and monitoring of CAR expression on the LV surface. This webinar is essential for professionals dedicated to improving quality and safety of cell therapies.<blockquote>Presenter: Dr. Alex Shephard (Market Manager, Cell Therapy, Unchained Labs)Presenter:&nbsp;Dr. Adam Inche (Founder &amp; CEO, Lentitek)</blockquote>

Unchained Labs: Preventing the danger of unwanted CAR expression during lentivirus production

Preventing the danger of unwanted CAR expression during lentivirus production

Join this exclusive webinar to discover advanced strategies for enhancing the quality of lentiviral (LV) vectors in cell therapy manufacturing. 