Changes In Manufacturing Process Research Articles

(Invited) Chemical Mechanical Planarization Integrated Data Collaboration: Uncover Hidden Interactions for Predictive Maintenance and PCN

This article introduces an innovative analytical methodology that employs machine learning to optimize and predict consumable impacts for Chemical Mechanical Planarization (CMP). By harnessing fleet CMP equipment performance and individual equipment characteristics, our proposed approach aims to elevate wafer-level quality, maximize equipment utilization rates, and minimize unnecessary downtime. CMP, a multifaceted process, its performance is often influenced by strong interactions from its critical components including slurry, pad, machine recipe, and dresser usage. This requires control beyond hardware advancements, especially when equipment is pushed to its limits. Therefore, the demand for higher precision on-wafer performance mandates a data collaboration with sophisticated analytical strategy. In addition, a digitalized product change notification (PCN) concept is also introduced to demonstrate effectiveness of applying integrated data analytics collaboratively across semiconductor chain to accelerate material manufacturing process changes, minimizing impacts on wafer results and shortening the learning cycle and ramp time to full production.Our study leverages data analytics to explore differences between equipment within the same fleet of similar processing. Engineers can deploy a process based on the historical performance of specific equipment, supported by a model trained on data from the same fleet. Furthermore, our approach enables each equipment to predict its own fingerprinted consumable maintenance, accurately forecasting the maintenance time for consumable changes. This concept is equally applicable for consumable PCN migrations.The first use case is to demonstrate the use of integrated data for fleet matching of CMP equipment and/or consumable batches running similar processes. This is particularly crucial as the demand for process precision increases and the need to reduce post-CMP result variability in removal rates and wafer-level uniformity intensifies. This approach could add proactive data driven strategy for process engineers who traditionally concentrate on the removal rate, a highly influential factor, with the standard deviation of platen and machine data identified as a key parameter.The second use case employs heatmaps analysis and proposes scatter plots as an intuitive method to comprehend intricate connections between average removal rates and various parameters. Machine learning is particularly advantageous in this context, as no single parameter plays a dominant role. Preliminary observations suggested, for example that dresser and pad characteristics may have compounding impacts to the wafer level performance.In summary, this article provides a roadmap for in-depth CMP data analysis fed into machine learning, aiming to unravel trends and influential factors that can enhance process optimization and shorten the PCN qualification timeline to meet the increasing demands for CMP process precision and efficiency in High Volume Manufacturing (HVM).

Supporting Manufacturing Process Changes with an Innovative Microscopy Method

Abstract Bakelite Chemicals LLC has developed an innovative microscopy technique to view adhesives “in use.” The cornerstone of the method is based on sample preparation. Samples of a composite wood product are sanded to a highly polished surface using a progression of sandpaper grits from lowest to highest. This preparation technique differs significantly from historical preparation techniques, which rely on soaking or embedding samples followed by thin-section creation using a microtome. The wet preparation technique causes wood cells compressed during production of the composite to swell and change how the adhesive is seen within those cells. The addition of water to the sample can also move uncured adhesive around the bond line. These changes can significantly alter the interpretation of how the adhesive performs during the manufacturing process. The new preparation technique combined with standard fluorescence microscopy has provided a groundbreaking and accessible ability to understand how an adhesive responds to process changes in manufacturing. Improving the understanding of the dynamic relationship between the adhesive and manufacturing processes will be crucial in helping the wood products industry take advantage of the rapid improvements in processing technology.

Modeling the thermo-mechanical response and phase changes in metallic additive manufacturing (MAM) processes using a dissipative phase-field model

Additive manufacturing (AM) has emerged as a highly promising manufacturing technique, offering unprecedented possibilities for creating complex geometries and functional structures. However, harnessing the full potential of AM requires the development of a robust computational framework capable of capturing the intricate multi-scale and multi-physics nature of the process. The constitutive and structural responses encountered in AM are particularly challenging to reproduce due to the complex behavior of the material involved. This research aims to address these challenges by presenting a comprehensive computational approach that incorporates a material model capable of accurately representing the behavior of different phases occurring during AM. To achieve this, the finite element method, using the Lagrangian framework in the implicit time scheme, is employed through the widely adopted ABAQUS software. Computational implementation is facilitated using the FORTRAN programming language. By employing weakly coupled thermal and mechanical constitutive equations, the framework enables the analysis of thermal stresses, strains, and displacements during realistic solidification processes, which inherently involve highly nonlinear constitutive relations. Through a series of numerical examples, the capabilities of the proposed model are demonstrated across various computational scales, particularly during the rapid melting and solidification phases. These simulations reveal the formation of residual stresses, which can lead to part distortion and have detrimental effects on the mechanical properties of the manufactured components. This research contributes to the advancement of additive manufacturing by providing a reliable computational tool that integrates the complex interplay between thermal and mechanical phenomena. The developed framework enhances our understanding of the AM process, offering valuable insights into the factors influencing the structural integrity and performance of additively manufactured parts.

An Industry Perspective on the use of Forced Degradation Studies to Assess Comparability of Biopharmaceuticals

Forced degradation, also known as stress testing, is used throughout pharmaceutical development for many purposes including assessing the comparability of biopharmaceutical products according to ICH Guideline Q5E. These formal comparability studies, the results of which are submitted to health authorities, investigate potential impacts of manufacturing process changes on the quality, safety, and efficacy of the drug. Despite the wide use of forced degradation in comparability assessments, detailed guidance on the design and interpretation of such studies is scarce. The BioPhorum Development Group is an industry-wide consortium enabling networking and sharing of common practices for the development of biopharmaceuticals. The BioPhorum Development Group Forced Degradation Workstream recently conducted several group discussions and a benchmarking survey to understand current industry approaches for the use of forced degradation studies to assess comparability of protein-based biopharmaceuticals. The results provide insight into the design of forced degradation studies, analytical characterization and testing strategies, data evaluation criteria, as well as some considerations and differences for non-platform modalities (e.g., non-traditional mAbs). This article presents survey responses from several global companies of various sizes and provides an industry perspective and experience regarding the practicalities of using forced degradation to assess comparability.

Oligonucleotide mapping via mass spectrometry to enable comprehensive primary structure characterization of an mRNA vaccine against SARS-CoV-2

Oligonucleotide mapping via liquid chromatography with UV detection coupled to tandem mass spectrometry (LC-UV-MS/MS) was recently developed to support development of Comirnaty, the world’s first commercial mRNA vaccine which immunizes against the SARS-CoV-2 virus. Analogous to peptide mapping of therapeutic protein modalities, oligonucleotide mapping described here provides direct primary structure characterization of mRNA, through enzymatic digestion, accurate mass determinations, and optimized collisionally-induced fragmentation. Sample preparation for oligonucleotide mapping is a rapid, one-pot, one-enzyme digestion. The digest is analyzed via LC-MS/MS with an extended gradient and resulting data analysis employs semi-automated software. In a single method, oligonucleotide mapping readouts include a highly reproducible and completely annotated UV chromatogram with 100% maximum sequence coverage, and a microheterogeneity assessment of 5′ terminus capping and 3′ terminus poly(A)-tail length. Oligonucleotide mapping was pivotal to ensure the quality, safety, and efficacy of mRNA vaccines by providing: confirmation of construct identity and primary structure and assessment of product comparability following manufacturing process changes. More broadly, this technique may be used to directly interrogate the primary structure of RNA molecules in general.

Safety and clinical outcomes in children with acid sphingomyelinase deficiency were not impacted by a change in the olipudase alfa drug manufacturing process: ASCEND-Peds 1-year subanalysis

Safety and clinical outcomes in children with acid sphingomyelinase deficiency were not impacted by a change in the olipudase alfa drug manufacturing process: ASCEND-Peds 1-year subanalysis

Human Factors and Ergonomics in Manufacturing in the Industry

Manufacturing industries have experienced rapid technological advancement and growth as a result of the Industry 4.0 revolution. Changes in human work and efficient manufacturing processes brought about by technological advancement may pose new threats to employee well-being and test existing knowledge and skills. The scientific field of human factors and ergonomics (HF/E) aims to simultaneously improve both the overall performance of the system and the well-being of employees in a variety of workplace settings. The purpose of this scoping review is to provide an overview of the most recent HF/E research on the manufacturing industry 4.0 context.37 of the 336 research articles were analyzed with the help of a human-centric work system framework from the HF/E literature. In micro- and macro ergonomics work system frameworks, difficulties arising from technological advancement were examined. To optimize overall sociotechnical work system performance in the context of rapid technological development in manufacturing industries, we frame characteristics of an organization level maturity model on the basis of the review.

REAL-WORLD UTILIZATION OF IMMUNE GLOBULIN INTRAVENOUS 10% AT PHYSICIAN OFFICE INFUSION CENTERS

<h3>Introduction</h3> Immune Globulin Intravenous (human) 10% liquid (IGIV 10%) was FDA-approved in 2012, voluntarily withdrawn in 2016, and reintroduced in 2019 by a new manufacturer with an optimized manufacturing process. Given the manufacturing process changes and utilization of the product in the US, the assessment of post-marketing clinical experience is warranted. The objective of this study is to evaluate post-marketing tolerability of IVIG 10% in a real-world setting. <h3>Methods</h3> We conducted a retrospective observational review of a random sample of patients who received IGIV 10% from 8/2021-5/2022 at physician office infusion centers (OICs) throughout the US. Study data from electronic medical records included demographics, therapy details, and infusion-related adverse events (AEs). <h3>Results</h3> Twenty-three of 96 IGIV 10% patients were randomly-selected from 9 OICs. The mean age was 74±5.3 years with 78% female. Common comorbidities included hypertension (74%) and gastroesophageal reflux disease (61%). One patient was immune globulin (IG) naïve, and 22 patients (96%) were IG-treatment experienced. Most (91%) had primary immunodeficiencies, with one chronic lymphocytic leukemia and one dermatomyositis. The mean IGIV 10% dose was 432±129.2 infused every three or four weeks. IGIV 10% infusions were titrated over an average of 78±28.8 minutes with an average maximum infusion rate of 154±18.8 mL/hr. During the study, patients received a mean of 7±2 infusions. Of 155 infusions, five AEs were reported (fatigue, headache, nausea, dizziness) during 4 infusions (17%) for an overall AE rate per infusion of 3%. <h3>Conclusions</h3> IGIV 10% was successfully administered to patients in OICs and was well-tolerated over multiple infusions.

Macro-Micro Coupled Simulation of SLM Process with Inconel 718 Superalloy

As an increasingly mature additive manufacturing technology for metal materials, Selective Laser Melting (SLM) technology has become a hot topic in many application fields. However, due to the fast-moving velocity and small scale of the laser beam in the SLM process, it is very difficult to directly observe the microstructural changes in the SLM additive manufacturing process. In this study, a macro-micro coupled simulation model of Inconel 718 SLM process was established to study the solidification behavior of the molten pool. The macro temperature field is obtained by the finite difference method based on the birth and death grid algorithm. The local temperature intercepted from the macro temperature field is employed as the input condition for phase field microstructure calculation. Dendrite morphology, intercellular spacing, and microsegregation are simulated under the coupled model. The result shows that the solidification structure of IN718 alloy in the micro molten pool formed by SLM grows in the form of a non-flat interface. The primary dendrite spacing predicted by the simulation is in good agreement with Hunt model at the initial stage of solidification. The solute trapping caused by non-equilibrium solidification makes dendrites dissolve more Nb, resulting in microsegregation.

Using Tiny-TIM Dissolution and In Silico Simulation to Accelerate Oral Product Development of a BCS Class II Compound.

Though oral drug delivery is the most preferred route of administration, there is high drug pharmacokinetic variability associated with the oral route. Change in drug substance particle size distribution, formulation composition, or manufacturing process may impact the dissolution and, hence, the systemic drug absorption in biopharmaceutics classification system class II compounds. In the present research, using a Boehringer Ingelheim investigational drug substance as the model compound, the tiny-TIM in vitro data and in silico pharmacokinetic model were used to establish in vitro-in vivo correlation and to predict the oral bioavailability. The level C in vitro-in vivo correlation between in vivo AUC and in vitro amount dissolved in both fasted and fed states could be established. Furthermore, level A in vitro-in vivo correlation was established between in vivo fraction absorbed and bioaccessibility from tiny-TIM dissolution in both fasted and fed states. Prediction of positive food effect from tiny-TIM dissolution was consistent with conclusion from clinical studies. Such predictive models developed using the minimum clinical data and the in vitro tiny-TIM data have the potential to reduce the animal and human experiments and to expedite the overall drug development process.

Epitope Profiling of Diphtheria Toxoid Provides Enhanced Monitoring for Consistency Testing during Manufacturing Process Changes.

In the vaccine industry, multiple physicochemical, immunological, in vitro and in vivo analytical methods are applied throughout the manufacturing process to characterize and monitor the quality of vaccines. Presented here is the Single Epitope Antigenicity Test (SEAT), an innovative, quantitative epitope profiling method which provides an extended immunochemical analysis for diphtheria toxoid (DTxd) to be used for consistency testing during manufacturing process changes. The method uses BioLayer Interferometry (BLI) and a panel of monoclonal antibodies (mAbs) to independently assess nine individual antigenic sites of DTxd. The panel includes mAbs which are functional, bind distinct sites on DTxd and are able to distinguish intact DTxd from that which has been exposed to heat treatment. The SEAT method was qualified for precision, accuracy, and linearity, and was used to define a preliminary comparability range for DTxd made using the current manufacturing process. DTxd lots manufactured using alternate processes were assessed in the context of this range to determine the impact on DTxd antigenicity. Epitope profiling by SEAT provides quantitative information on the integrity of multiple important antigenic regions of DTxd, and therefore represents a valuable tool in a comprehensive analytical test package which can be used to support manufacturing process changes for vaccines.

An audit of pharmaceutical continuous manufacturing regulatory submissions and outcomes in the US

Continuous manufacturing (CM) sends materials directly and continuously to the next step of a process, eliminating hold times and reducing processing times. The potential benefits of CM include improved product quality, reduced waste, lower costs, and increased manufacturing flexibility and agility. Some pharmaceutical manufacturers have been hesitant to adopt CM owing to perceived regulatory risks such as increased time to regulatory approval and market entry, more difficulty submitting postapproval changes, and higher inspectional scrutiny. An FDA self-audit of regulatory submissions in the U.S. examined the outcomes, at approval and during the product lifecycle, of continuous manufacturing applications as compared to traditional batch applications. There were no substantial regulatory barriers identified for CM applications related to manufacturing process changes or pre-approval inspections. CM applicants had relatively shorter times to approval and market as compared to similar batch applications, based on the mean or median times to approval (8 or 3 months faster) and marketing (12 or 4 months faster) from submission, translating to an estimated $171–537 M in early revenue benefit.

Annual trends in adverse events following mumps vaccination in Japan: A retrospective study

BackgroundIn Japan, a monovalent mumps vaccine is provided on a voluntary basis. Due to public concerns over post-vaccination aseptic meningitis, the vaccination coverage is not high enough. The present study investigated the incidence of adverse events, including aseptic meningitis, after Torii strain–derived mumps vaccination. MethodsThis retrospective, observational study used data collected by a vaccine manufacturer regarding adverse events following mumps vaccinations at medical institutions between 1992 and 2018. In addition, the number of Torii strain–derived mumps vaccines shipped each year was obtained. The incidence (per 100,000 doses) and 95% confidence intervals (CIs) were calculated for all adverse events and each adverse event, categorized as aseptic meningitis, encephalitis, mumps, mumps complications, and others. ResultsDuring the study period, 8,262,121 mumps vaccine doses were shipped, and 688 subjects reported adverse events. The incidence for all adverse events (per 100,000 doses) was 8.33, and the incidence was 4.19 for aseptic meningitis, 0.33 for encephalitis, 0.80 for mumps, 0.25 for mumps complications, and 3.78 for others. The incidence of aseptic meningitis (per 100,000 doses) was 7.90 (95% CI: 5.61–10.18) between 1998 and 2000 but declined by half, to 3.91 (2.46–5.36), between 2001 and 2003. The most recent incidence (per 100,000 doses) of aseptic meningitis, for the period 2016 to 2018, was 2.78 (1.94–3.62). ConclusionThe incidence of post-vaccination aseptic meningitis has declined significantly since 2001, and the incidence has remained stable at fewer than 3 cases per 100,000 doses since 2010. Multiple factors might have contributed to the decline in aseptic meningitis incidence, including (i) lowered misclassification of aseptic meningitis resulting from echovirus infection; (ii) changes in the vaccine manufacturing process in 2000; and (iii) publication in 2008 of the recommendation for vaccination of children at 1 year of age.

Predicting the impact of formation protocols on battery lifetime immediately after manufacturing

Predicting the impact of formation protocols on battery lifetime immediately after manufacturing

Predicting the Impact of Formation Protocols on Battery Lifetime Immediately After Manufacturing

Increasing the speed of battery formation can significantly lower lithium ion battery manufacturing costs. However, adopting faster formation protocols in real manufacturing settings is challenging due to a lack of inexpensive, rapid diagnostic signals that can inform possible impacts to long term battery lifetime. In this work, we identify the cell resistance measured at low states of charge as an early-life diagnostic feature for screening new formation protocols. We show that this signal correlates to cycle life and improves the accuracy of data-driven battery lifetime prediction models. The signal is obtainable at the end of the manufacturing line, takes seconds to acquire, and does not add any additional capital cost. We explore a physical connection between this resistance signal and the amount of lithium consumed during formation, which suggests that the technique may be broadly applicable for evaluating any battery manufacturing process or design change that could impact the total lithium consumed during formation. This work demonstrates that carefully engineered, simple features can provide useful diagnostics and prognostics for battery degradation at the beginning of life.

Green Nanofabrication Opportunities in the Semiconductor Industry: A Life Cycle Perspective.

The turn of the 21st century heralded in the semiconductor age alongside the Anthropocene epoch, characterised by the ever-increasing human impact on the environment. The ecological consequences of semiconductor chip manufacturing are the most predominant within the electronics industry. This is due to current reliance upon large amounts of solvents, acids and gases that have numerous toxicological impacts. Management and assessment of hazardous chemicals is complicated by trade secrets and continual rapid change in the electronic manufacturing process. Of the many subprocesses involved in chip manufacturing, lithographic processes are of particular concern. Current developments in bottom-up lithography, such as directed self-assembly (DSA) of block copolymers (BCPs), are being considered as a next-generation technology for semiconductor chip production. These nanofabrication techniques present a novel opportunity for improving the sustainability of lithography by reducing the number of processing steps, energy and chemical waste products involved. At present, to the extent of our knowledge, there is no published life cycle assessment (LCA) evaluating the environmental impact of new bottom-up lithography versus conventional lithographic techniques. Quantification of this impact is central to verifying whether these new nanofabrication routes can replace conventional deposition techniques in industry as a more environmentally friendly option.

In Vitro-In Vivo Correlation (IVIVC) Population Modeling for the In Silico Bioequivalence of a Long-Acting Release Formulation of Progesterone.

Health authorities carefully evaluate any change in the batch manufacturing process of a drug before and after regulatory approval. In the absence of an adequate in vitro–in vivo correlation (Level A IVIVC), an in vivo bioequivalence (BE) study is frequently required, increasing the cost and time of drug development. This study focused on developing a Level A IVIVC for progesterone vaginal rings (PVRs), a dosage form designed for the continuous delivery in vivo. The pharmacokinetics (PK) of four batches of rings charged with 125, 375, 750 and 1500 mg of progesterone and characterized by different in vitro release rates were evaluated in two clinical studies. In vivo serum concentrations and in vitro release profiles were used to develop a population IVIVC progesterone ring (P-ring) model through a direct differential-equation-based method and a nonlinear-mixed-effect approach. The in vivo release, , was predicted from the in vitro profile through a nonlinear relationship. was used as the input of a compartmental PK model describing the in vivo serum concentration dynamics of progesterone. The proposed IVIVC P-ring model was able to correctly predict the in vivo concentration–time profiles of progesterone starting from the in vitro PVR release profiles. Its internal and external predictability was carefully evaluated considering the FDA acceptance criteria for IVIVC assessment of extended-release oral drugs. Obtained results justified the use of the in vitro release testing in lieu of clinical studies for the BE assessment of any new PVRs batches. Finally, the possible use of the developed population IVIVC model as a simulator of virtual BE trials was explored through a case study.

Application of a Two-Analyte Integrated Population Pharmacokinetic Model to Evaluate the Impact of Intrinsic and Extrinsic Factors on the Pharmacokinetics of Polatuzumab Vedotin in Patients with Non-Hodgkin Lymphoma

PurposeThe established two-analyte integrated population pharmacokinetic model was applied to assess the impact of intrinsic/extrinsic factors on the pharmacokinetics (PK) of polatuzumab vedotin (pola) in patients with non-Hodgkin lymphoma (NHL) following bodyweight-based dosing.MethodsModel simulations based on individual empirical Bayes estimates were used to evaluate the impact of intrinsic/extrinsic factors as patient subgroups on Cycle 6 exposures. Intrinsic factors included bodyweight, age, sex, hepatic and renal functions. Extrinsic factors included rituximab/obinutuzumab or bendamustine combination with pola and manufacturing process. The predicted impact on exposures along with the established exposure-response relationships were used to assess clinical relevance.ResultsNo clinically meaningful differences in Cycle 6 pola exposures were found for the following subgroups: bodyweight 100–146 kg versus 38–<100 kg, age ≥ 65 years versus <65 years, female versus male, mild hepatic impairment versus normal, mild-to-moderate renal impairment versus normal. Co-administration of rituximab/obinutuzumab or bendamustine, and change in the pola manufacturing process, also had no meaningful impact on PK.ConclusionsIn patients with NHL, bodyweight-based dosing is adequate, and no further dose adjustment is recommended for the heavier subgroup (100–146 kg). In addition, no dose adjustments are recommended for other subgroups based on intrinsic/extrinsic factors evaluated.

Preparation of fully flexible lithium metal batteries with free-standing β-Na0.33V2O5 cathodes and LAGP hybrid solid electrolytes

Safe and flexible batteries are expected to be the enabler for advancing the technology of wearable electronics to an unforeseen level in near future. However, to date the energy density of such devices is rather limited due to the rather large proportion of dead weight and volume to provide good flexibility. To overcome this hurdle, a disruptive change in the battery manufacturing process is needed. Herein, we not only introduce a simple phase inversion method for the preparation of free-standing and flexible β-Na0.33V2O5 cathodes without metal current collector, but also demonstrate the possibility to integrate those into fully flexible lithium metal batteries. Additionally, employing a LAGP-based hybrid solid electrolyte enables excellent high temperature stability and thus, enhanced safety characteristics of the device. Such integrated flexible batteries exhibit fast and stable lithium-ion storage capabilities, with a large specific capacity of 228mAh g−1 at 0.1C and excellent cycling stability translating into an outstanding specific energy of 407.8 Wh kg−1 on electrode level.

In vitro-in vivo correlation of parenteral PLGA microspheres: Effect of variable burst release

Development of IVIVCs is a very complicated process, especially for complex drug products such as parenteral PLGA microspheres with multiphasic drug release characteristics. Specifically, microspheres that exhibit an initial burst release phase are even more challenging since the in vitro and in vivo burst release phases may not be comparable if drug absorption is rate-limiting at this stage. Therefore, the objectives of the present work were: 1) to investigate the predictability of developed IVIVCs for the in vivo burst release phase based on the in vitro burst release phase of the formulations; and 2) to evaluate the impact of variable burst release on the predictability of the developed IVIVCs for two different types of microsphere-based drug products. Accordingly, Risperdal Consta® (Risperidone) and Lupron Depot® (Leuprolide acetate, LA) were selected as model products. Compositionally equivalent risperidone and LA formulations with variable burst release phases were prepared with manufacturing process changes (such as solvent systems and mixing methods). The prepared microspheres exhibited differences in critical physicochemical properties (such as particle size, porosity, average pore diameter, and drug distribution) and hence differences in their in vitro release characteristics (such as variable burst release and release rate). The in vitro and in vivo (rabbit model (intramuscular injection) burst release were similar for the risperidone microspheres but were significantly different for the LA microspheres. This had an impact on the complexity of the developed IVIVC models. Level A IVIVCs with the ability to predict various types of burst release were developed using time scaling and shifting factors. Moreover, it was observed that IVIVCs developed using formulations with less variation in burst release had better predictability and vice-versa. Thus, the present research has provided a comprehensive understanding of the impact of the burst release phase on the development, complexity, and predictability of IVIVCs for complex parenteral microspheres containing a variety of therapeutic molecules.